The geography of EU discontent.
Date: 2018-12-16
Institutions: Directorate-General for Regional and Urban Policy
Subjects: European Union, declining industrial region, economic recession, education, euroscepticism, migration, populism, vote

THE GEOGRAPHY 
OF EU DISCONTENT

LEWIS DIJKSTRA, HUGO POELMAN  AND 
ANDRÉS RODRÍGUEZ-POSE 

Working Papers

A series of short papers on regional 
research and indicators produced 
by the Directorate-General for 
Regional and Urban Policy

WP 12/2018

Regional and
Urban Policy

 
EXECUTIVE SUMMARY

Over the last decade, political parties opposed to EU integration have almost doubled their votes. 
The general opinion of the EU has also deteriorated, revealing a growing number of people who distrust 
the Union. To understand this development, this paper focuses on the geography of EU discontent. For the 
first time, it maps the vote against EU integration in the last national elections across more than 
63 000 electoral districts in each of the 28 EU Member States. It assesses whether a range of factors 
considered to have fostered the surge in populism have had an impact on anti-EU voting. Research into 
populism often relies on the individual characteristics of anti-system voters: older, working-class, male 
voters on low incomes and with few qualifications to cope with the challenges of a modern economy. The 
results  show  that  economic  and  industrial  decline  are  driving  the  anti-EU  vote.  Areas  with  lower 
employment rates or with a less-educated workforce are also more likely to vote anti-EU. Once these 
factors have been taken into account, many of the purported causes of the geography of discontent either 
matter much less than expected or their impact varies depending on the strength of opposition to the 
European project.

Keywords:  Anti-Europeanism,  anti-system  voting,  populism,  economic  decline,  industrial  decline, 
education, migration, European Union

CONTENTS

  1  Growing disenchantment with the European Union 
  2  Vote against EU integration and vote for populist parties: linked but distinct 
  3  The theories behind what determines the rise of the anti-system and anti-EU vote 
  4  Proving the theories behind the geography of EU discontent 
  5  What drives the votes against EU integration? 
  6  Discussion 
  7  Conclusions 
  References 

2
5
11
13
15
19
20
21

LEGAL NOTICE

This document has been prepared for the European Commission however it reflects the views only of the 
authors, and the Commission cannot be held responsible for any use which may be made of the informa-
tion contained therein.

More information on the European Union is available on the Internet (http://www.europa.eu).

Luxembourg: Publications Office of the European Union, 2018

© Cover image: Ababsolutum / iStockphoto.com

© European Union, 2018

Reproduction is authorised provided the source is acknowledged.

 
T H E   G E O G R A P H Y   O F   E U   D I S C O N T E N T

1

Introduction

This article provides the first comprehensive overview of the anti-EU vote across the entire European 
Union (EU) with a detailed geographical breakdown. We map the share of votes for parties that opposed 
EU integration in the last national election between 2013 and 2018 across more than 63 000 electoral 
districts in the 28 EU Member States. We distinguish between three different levels of EU opposition: 
strongly opposed, opposed, and somewhat opposed. The share of the anti-EU vote is then regressed on 
a series of factors that reflect the three dominant explanations of anti-system votes in Europe: the 
personal characteristics of people ‘left-behind’, disparities in age, education and income, and different 
types of long-term territorial decline. 

The results of the analysis indicate that the anti-EU vote is mainly driven by a combination of long-term 
economic and industrial decline, low levels of education, and a lack of local employment opportunities. 
Once these factors are taken into consideration, well-off places are more likely to vote for anti-EU 
parties than places that are worse off, in contrast to explanations linking anti-establishment voting with 
poor people living in poor places. Moreover, other factors that have featured prominently as drivers of 
populism – such as ageing, rurality, remoteness, employment decline, and population decline – seem to 
matter much less or matter in different ways (depending on the strength of opposition to EU integration 
taken into consideration). 

To demonstrate this, the article adopts the following structure. The first section describes how public 
opinion of the EU has deteriorated over the past 15 years, how anti-EU votes have grown, and how this 
is linked to, although differs from, voting for populist parties. The following section analyses the vote for 
parties standing against EU integration, and is followed by an overview of the factors linked to anti-EU 
voting.  Sections  4  and  5  look  at  the  method  and  data  and  present  the  results  of  the  analysis, 
respectively. The final sections discuss the results, give a recap on the reasons behind the geography of 
EU discontent, and offer some conclusions and policy implications.

2

1. 

 GROWING 
DISENCHANTMENT 
WITH THE EUROPEAN 
UNION 

On 24 June 2016, citizens of United Kingdom and the rest of 
the world woke up to the news that Britain had voted by a slim 
majority to leave the EU. This came as a huge surprise as, 
although many polls had predicted a tight outcome in the 
vote,  the  overwhelming  expectation  –  including  by  most 
leaders of the leave vote – was that Britain would remain in 
the EU. It showed that support from most UK parties – albeit 
often  distinctly  lukewarm  or  ambivalent  –  for  the  remain 
option and the benefits of remaining in the EU trumpeted by 
a  multitude  of  experts  were  not  enough  to  win  the 
referendum. The outcome has been described in many ways, 
from  the  will  of  the  people  to  a  flawed  result  based  on 
misinformation, but its consequences will profoundly shape 
the future of the UK and the rest of the EU. 

Furthermore, public opinion in the UK around the time of the 
referendum  was  not  the  most  anti-EU.  In  2016,  in  seven 
Member States, more people tended not trust the EU than in 
the UK (Eurobarometer). This led to heightened speculation 
about other referenda on leaving the EU.  

However, the Brexit vote was not the first sign of growing 
disenchantment with the EU. The share of votes for parties 
opposed to EU integration, as defined by the Chapel Hill Expert 
Survey1,  has  steadily  increased  over  the  last  15  years 
(Figure  1).  The  vote  for  parties  (strongly)  opposed  to  EU 
integration grew from 10 % to 18 % between 2000 and 2018. 
The same upward trend remains if we include the parties 
somewhat opposed to EU integration: from 15 % in 2000 to 
26 % in 2018. This is not the result of more votes in the UK 
going to anti-EU parties (although they did). The share of the 
vote against EU integration increased by almost the same in 
the EU without the UK figures.

Parties (strongly) opposed to European integration tend to 
advocate leaving the EU – as has been the case with UKIP, the 
Dutch  Party  for  Freedom,  or  the  French  Front  National,  or 
a scaling back of the EU to a loose confederation of states – 
as  posited  by  the  Italian  Lega,  the  German  AfD,  or  the 
Hungarian  Jobbik2.  Parties  that  are  somewhat  opposed  to 
European integration – such as the Italian Five Star Movement 
(MoVimento  5  Stelle),  the  Hungarian  Fidesz,  and  the  UK 
Conservatives  (prior  to  the  referendum)  –  want  the  EU  to 
change substantially but they do not necessarily advocate 
leaving  the  Union  or  turning  it  into  a  loose  coalition  of 
sovereign states. 

The increase in the vote for parties opposed to EU integration 
is, in part, a reflection of changing public opinion. In 2004, 
only 28 % of the population aged 15 and over did not trust the 
EU. This share rose to 47 % in 2012 but dropped back to 39 % 
in 2018. Between 2004 and 2018, the share of population 
distrusting  the  EU  increased  by  more  than  20  percentage 
points in nine Member States (Figure 2). In Greece, the level of 
distrust went up by 48 percentage points. As a result, two 
thirds of the Greek population tend not to trust the EU, the 
highest  share  among  EU  Member  States.  In  Greece,  this 
opinion is also reflected in the high share of votes for parties 
against EU integration, although this is not always the case. 
Denmark, for example, has one of the lowest levels of distrust 
but one of the highest shares of votes for parties (strongly) 
opposed to EU integration (Figures 3 and 4). In Spain, the 
opposite is the case: it has the fifth highest distrust of the 
Union but no significant party as yet against EU integration 
(Figures 3 and 4). 

1. 

2. 

The Chapel Hill Expert Survey (CHES) assesses the orientation of political parties on a variety of issues – ranging from political orientation to position on 
specific topics. The 1999-2014 trend file and 2107 surveys cover the political parties that received at least 5 % of the vote in the election prior to the as-
sessment. For the 2014 exercise, 337 experts assessed 268 parties in the EU-28. The election years covered per EU Member State are listed in Appendix 1. 
The 40 most anti-European parties, according to their score, are listed in Appendix 2.

These descriptions are based on the CHES assessment made in 2014 or 2017 and may no longer correspond to the current position of these parties.

3

2004

2018

FIGURE 1: Share of vote for parties that oppose EU integration in the EU-28, 2000-2018

%
n

i

,

s
e
t
o
v

f
o

e
r
a
h
S

30

25

20

15

10

5

0

(somewhat) opposed

(strongly) opposed

0
0
0
2

1
0
0
2

2
0
0
2

3
0
0
2

4
0
0
2

5
0
0
2

6
0
0
2

7
0
0
2

8
0
0
2

9
0
0
2

0
1
0
2

1
1
0
2

2
1
0
2

3
1
0
2

4
1
0
2

5
1
0
2

6
1
0
2

7
1
0
2

8
1
0
2

Source: Own elaboration on CHES data and national sources

FIGURE 2: Share of the population tending not to trust the EU, 2004-2018

r
e
v
o

d
n
a
5
1
d
e
g
a
n
o
i
t
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70%

60%

50%

40%

30%

20%

10%

0%

LT EE DK LU SE FI MT IE BG NL PT LV RO DE PL HU BE HR SK IT CY FR AT ES UK CZ SI EL

EU

Source: Own elaborations based on Eurobarometer data

THE GEOGRAPHY OF EU DISCONTENT 
 
 
 
 
 
 
 
 
 
4

FIGURE 3: Votes for parties (strongly) opposed to EU integration and lack of trust in the EU

35

30

25

20

15

10

5

0

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t

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1
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3
1
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n
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a
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n

i

U
E

DK

SE

FI

AT

FR

IT

HU

CZ

NL

BG

PL

IE

EU

DE

UK

PT

SK

EL

MT

LT

EE

LU

RO

LV

BE

HR

15

25

35

45

CY

SI

ES

55

65

75

Tend not to trust the EU average 2014-2018, 
in % of population 15 and older

FIGURE 4: Votes for parties (somewhat) opposed to EU integration and lack of trust in the EU

70

60

50

40

30

20

10

o
t

d
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FR

SK

CZ

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PT

DE

BE

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HR

RO

0

15

25

35

45

SI

CY

ES

55

65

75

Tend not to trust the EU average 2014-2018, 
in % of population 15 and older

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5

Some countries, such as Cyprus, Malta, Romania, Slovenia and 
Spain,  have  so  far  remained  immune  to  the  anti-EU  wave. 
In Croatia and the Baltic countries, Euroscepticism remains 
marginal with less than 5 % attributed to parties (somewhat) 
opposed to EU integration. But these countries are increasingly 
the exception rather than the rule (Figure 5). 

By measuring the share of the anti-EU vote in the last national 
legislative elections in over 63 000 electoral constituencies we 
are  able  to  create  a  detailed  map  of  the  geography  of  EU 
discontent (Figure 6). 

2. 

 VOTE AGAINST EU 
INTEGRATION AND 
VOTE FOR POPULIST 
PARTIES: LINKED BUT 
DISTINCT 

2.1. 

 VOTING AGAINST EU INTEGRATION

In many EU Member States, parties (strongly) opposed to EU 
integration have become a force to be reckoned with, having 
collected  more  than  25 %  of  the  vote  in  the  last  national 
election3 in three EU Member States: Austria, Denmark and 
France (Figure 5). If those parties that are somewhat opposed 
to European integration are included, 10 Member States had a 
share of over 25 %. In Greece, Hungary, Italy and the UK the 
share was over 50 % (Figure 5).

FIGURE 5: Votes by party position on EU integration, 2013-2018

%
n

i

,

s
e
t
o
v

f
o

e
r
a
h
S

100

90

80

70

60

50

40

30

20

10

0

MT ES SI RO CY HR LV LT LU EE BE IE PL SK PT BG UK DE NL EL FI SE CZ HU IT FR AT DK
Countries are ranked by vote share (strongly) opposed, somewhat opposed, (somewhat) in favour.

EU

unknown

somewhat in favour

opposed

strongly in favour

neutral

strongly opposed

in favour

somewhat opposed

Source: Own elaboration on CHES data and national sources

3. 

The elections taken into consideration in the analysis took place from 2013 to 2018. In this and the following sections, the 2017 UK election was excluded as 
we wanted to analyse links without the result of the Brexit referendum on UK politics.

THE GEOGRAPHY OF EU DISCONTENT 
 
 
 
6

FIGURE 6: Share of the vote for parties opposed or strongly opposed to European integration (2013-2018)

7

Votes for parties opposed and strongly opposed to European 
integration are spread across many parts of the EU. Southern 
Denmark, Northern Italy, Southern Austria, Eastern Germany, 
Eastern Hungary or Southern Portugal are hot spots for anti-EU 
voting. Rural areas and small towns are more Eurosceptic than 
bigger cities. The anti-European vote is far lower in Lille, Metz, 
Nancy  and  Strasbourg  than  in  the  surrounding  countryside 
(Figure 6). The same applies in East Germany where the anti-
European vote is far less prominent in Berlin, Dresden and 
Leipzig  than  in  the  surrounding  areas,  or  in  Northern  Italy, 
pitching the two largest cities in the area – Milan and Turin – 
against  a  large  number  of  medium-sized  cities,  such  as 
Bergamo, Brescia, Cremona, Mantua, Pavia and Vercelli, and 
smaller cities and rural areas. Northern and Eastern Denmark, 
Sweden, Finland and Czechia also have a strong presence of 
radical anti-European parties. 

When the share of votes for moderate anti-European parties is 
taken into consideration, the panorama changes substantially 
(Figure 7). The geography of votes for parties moderately opposed 
to European integration almost fully encompasses the whole of 
Greece, Hungary and Italy. Here, the moderate anti-Europeans in 
Syriza, Fidesz and the Five Star Movement (in coalition with the 
more radically anti-EU integration Lega), respectively, secured 
power after the last election. Many areas of the UK are also at this 
level, while more than one fifth of the electorate in large swaths 
of Czechia, the Netherlands, France, Austria, southern Denmark, 
and Slovakia voted for anti-European parties. 

Lower shares of moderate anti-Europeanism are found in Poland, 
West  Germany,  Ireland  and  Portugal,  while  Spain,  Romania, 
Croatia, Slovenia and most of the Baltics have, to date, been 
relatively spared from all types of anti-Europeanism (Figure 7).

Votes for parties strongly opposed to European integration are 
virtually non-existent in Spain, the Baltics, Poland, Slovenia, 
Croatia, Romania, Belgium and Ireland. It is also much less of 
an issue in West Germany (and, especially in its north-western 
fringe), Bulgaria, Northern Portugal and Slovakia. 

Another factor worth noting is that the presence of moderately 
anti-EU parties, pervasive in the UK, Greece, Hungary, Czechia, 
Slovakia, the Netherlands, Italy and Poland, is almost non-
existent in places like Germany, Bulgaria, Finland and Denmark, 
and only a minor phenomenon in Sweden (Figure 7).  

THE GEOGRAPHY OF EU DISCONTENT8

FIGURE 7:  Share of vote for parties somewhat opposed, opposed, or strongly opposed to European 

integration (2013-2018)

9

2.2.  POPULISM IN THE EU 

What determines whether a vote for a given party is a populist 
or an anti-system vote? Defining populism is hotly debated 
within political science, with the very use of the term coming 
under scrutiny. In general, populist or anti-system parties pitch 
the ‘people’ against supposedly self-interested and sometime 
aloof ‘elites’. In defining the ‘people’ and ‘elites’, populist parties 
create a dichotomy of ‘us’ against ‘them’, identifying ‘them’ or 
‘the other’ as the antagonist and foe. 

The 2014 and 2017 Chapel Hill Expert Surveys assessed the 
role of anti-establishment and anti-elite rhetoric, often used as 
a proxy for identifying populist parties. Each political party 
received  a  score  between  0  (not  at  all  important)  and 
10 (extremely important). Earlier surveys did not include this 
indicator, which means that a trend analysis is not possible. 

In the latest national elections, strong populism (rounded score 
of 10) captured 9 % of the vote. Adding populist parties (score 
of 9) doubled the share to 18 %. Including somewhat populist 
parties (score of 8), pushed the share up to almost a quarter 
(23 %) of the votes coded by CHES.

Most populist parties are also anti-European integration (Polk 
and  Rovny,  2017).  It  is  increasingly  argued  that  ‘European 
integration contributes to the emergence of populism – and 
hence, to the rise of Euroscepticism as a form of populism – by 
destabilizing domestic party systems’ (Leconte, 2015: 256). 
Buti and Pichelmann (2017:4) go even further, asserting that 
‘the EU has become a popular “punch bag”, an easy target and 
prey’ for populist rhetoric. Parties at the extreme right and left 
of  the  political  spectrum  agree  in  portraying  ‘the  faceless 
bureaucrats of Brussels as the “other”’ (Rodrik, 2018: 24). The 
EU is therefore identified – together with migrants – as the 
main opponent. In party programme after party programme, 
electoral manifesto after electoral manifesto, the EU is depicted 
as a threat to national identity, to democracy, and even to 
economic stability and progress.

The  Dutch  Freedom  Party  in  its  very  short  2017-2021 
manifesto puts the aim of taking the Netherlands out of the EU 
as its second objective (Partij voor der Vrijheid, 2017). Similarly, 
the  UK  Independence  Party  (UKIP)  has  promoted  ‘a  Britain 
released from the shackles of the interfering EU’ (UKIP 2015 
Manifesto: 5). The French Rassemblement National, when it was 
still the Front National, had as it first objective of 144 electoral 
promises ‘to restore France’s national sovereignty [by creating] 
a Europe of independent nations, at the service of the peoples’ 
(2017: 3). This implied regaining ‘our freedom and the control 
of our destiny by restoring to the French people their (monetary, 
legislative, territorial, economic) sovereignty’ (2017:3).

Other  populist  and  anti-system  parties  do  not  necessarily 
advocate the abolition of or withdrawal from the EU, but blame 
many  of  the  current  real  or  perceived  ills  on  European 
integration.  The  2016  ‘Manifesto  for  Germany’  of  the 
Alternative  für  Deutschland  (AfD)  states  that  ‘the  EU  has 

become an undemocratic entity, whose policies are determined 
by bureaucrats who have no democratic accountability’ (p. 16) 
and, therefore, it should be downgraded to ‘an economic union 
based on shared interests, and consisting of sovereign, but 
loosely  connected  nation  states’  (p.  15).  The  Italian  Lega 
considers ‘the EU a gigantic supranational body, devoid of true 
democratic  legitimacy  and  structured  through  a  sprawling 
bureaucratic  structure  that  dictates  the  agenda  to  our 
governments even at the expense of the physical and economic 
protection  of  the  citizens  of  the  individual  Member  States’ 
(Lega, 2018). The Dutch Socialist Party (SP) considers European 
integration as a threat to democracy and the national welfare 
state and the party does not ‘want to sacrifice our democracy 
and welfare state on the Brussels altar’ (SP, 2018).

The biggest symbol of European economic integration, the euro, 
is also a target for most anti-establishment parties. The AfD 
(2016:  18)  posits  that  ‘the  euro  actually  jeopardises  the 
peaceful  co-existence  of  those  European  nations  who  are 
forced into sharing a common destiny by the Eurocracy’ and 
calls  ‘for  an  end  to  the  euro  experiment  and  its  orderly 
dissolution’ (2016: 17). Similarly, the Lega identifies ‘the euro 
[as]  the  main  cause  of  our  economic  decline,  a  currency 
designed for Germany and multinationals and contrary to the 
needs of Italy and the small business’ (Lega, 2018). And, from 
the other end of the political spectrum, the Dutch SP argues 
that ‘we should stop prioritising the survival of the euro and the 
short-term economic interests of large companies, banks and 
shareholders’ (SP, 2018).

Members of the Italian Five Star Movement also have European 
integration in their sight. For them, the crisis profoundly altered 
the balance of power in Europe, meaning that ‘today the EU is 
influenced by a small group of states, thus affecting the very 
democratic  character  of  the  EU  institutions’  (MoVimento 
5 Stelle, 2018: 2). 

Similar arguments are being reproduced in populist manifestos 
across  Europe.  This  is  the  case  for  the  Danish  Red-Green 
Alliance or the Danish People’s Party (Dansk Folkeparti), the 
Communist  Party  of  Greece,  Golden  Dawn,  or  Independent 
Greeks,  the  Austrian  Freedom  Party,  Hungary’s  Jobbik,  the 
Sweden Democrats and the Swedish Left Party, the Portuguese 
Unitary Democratic Coalition, and many other smaller anti-
system parties (see Appendix 2 for a list of the 40 most anti-
European parties included in the analysis and their degree of 
Euroscepticism).

Despite the links between populism and anti-EU voting, the two 
issues  are  nevertheless  distinct.  For  example,  the  Spanish 
Podemos  scores  high  on  anti-elite  and  anti-establishment 
rhetoric in CHES, but is also rated as somewhat in favour of EU 
integration. The UK Conservatives (2014 rating), the Czech ODS 
(Civic Democratic Party), and the Dutch Christenunie all score 
very low on the use of anti-elite rhetoric but are somewhat 
against EU integration. The two issues are statistically correlated, 
but populism only ‘explains’ about half of the variation in anti-EU 
voting (R2 of 0.48) (Figure 8, see also Appendix 4).

THE GEOGRAPHY OF EU DISCONTENT10

FIGURE 8:  Votes against EU integration and populist parties EU-28, 2013-2018

 10

  F r o n t 
F R , 
N a t i o n a l 
U K I P 
  J o b b i k 
H U , 
I T , 
  L E G A 

  A f D 
D E , 

  C i n q u e 
I T , 
L a 
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I n s o u m i s e 

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A T , 

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C Z , 

  S y r i z a 
E L , 

  P O D E M O S 
E S , 

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P L , 
  D I E 
D E , 

  L I N K E 

  R é p u b l i c a i n s 
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F R , 
  C S U 
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  F D P 
D E , 
I T , 
  F O R Z A 

  + 
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  1 0 . 2 1 3 
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  = 
R ² 

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  C i u d a d a n o s 
E S , 
F R , 
  M a r c h e 
  e n 

  L a b o u r 
U K , 

R O , 

  S P D 
D E , 
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I T , 
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D E , 
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  P l a t f o r m 
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P L , 
E S , 
  P P 

1.0

2.0

3.0

4.0

5.0

6.0

7.0

European integration, 1 = strongly opposed, 7 = strongly in favour

Finally, when using a narrow definition for both, the link almost 
disappears:

 Ý Only 20 % of the vote for the most populist parties goes to 

parties that are strongly opposed EU integration;

 Ý Only a third (35 %) of the vote for the most populist parties 

goes to parties that are also strongly opposed to EU 
integration.

The overlap between anti-EU voting and populism depends 
greatly on which measures of both factors are considered. 
When a narrow definition of one dimension and a broad one of 
the other is used, there is almost a perfect overlap:

 Ý

 Almost the entire vote (98 %) for the most populist 
parties (10) in the EU also goes to parties that are at least 
somewhat opposed to EU integration;

 Ý Almost the entire vote (99 %) for parties strongly opposed 
to EU integration also goes to parties that are at least 
somewhat populist (8-10). 

When using a broad definition for both, the overlap weakens:

 Ý Most (83 %) of the vote for somewhat populist parties also 
goes to parties that are at least somewhat opposed to EU 
integration; 

 Ý Only two thirds (69 %) of the vote for parties somewhat 

opposed to EU integration goes to parties that are at least 
somewhat populist (7-10). 

  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
11

3. 

 THE THEORIES 
BEHIND WHAT 
DETERMINES THE RISE 
OF THE ANTI-SYSTEM 
AND ANTI-EU VOTE

To  identify  the  main  causes  of  the  vote  against  European 
integration, we combine the theories proposed in the research 
on anti-EU voting – such as the Brexit vote – with research into 
populism in Europe and beyond. Two types of explanations, not 
mutually exclusive, emerge from this literature. 

First  and  foremost,  research  has  focused  on  the  individual 
characteristics of the anti-establishment voters. The archetype 
of  the  anti-system  supporter  has  been  identified  as  ‘older, 
working-class, white voters, citizens with few qualiﬁcations, who 
live on low incomes and lack the skills that are required to adapt 
and  prosper  amid  the  modern,  post-industrial  economy’ 
(Goodwin & Heath, 2016: 325). Thus, the individuals left behind 
by the modern economy and processes are much more likely to 
turn to or find shelter in anti-establishment political options: 
‘such “left-behind” voters feel cut adrift by the convergence of 
the main parties on a socially liberal, multicultural consensus, 
a worldview that is alien to them’ (Ford and Goodwin, 2017: 19). 

Several factors have been identified as the individual features 
of those left behind. Age is one of the two most important 
(Goodwin and Heath, 2016; Hobolt, 2016; Ford and Goodwin, 
2017; Essletzbichler et al., 2018; Gordon, 2018). Older voters 
are frequently portrayed as less capable of understanding or 
coping with economic change, multiculturalism, or immigration 
(Hobolt, 2016: 148; see also Ford and Goodwin, 2014) and, 
thus,  more  capable  of  displaying  culturally  conservative 
reactions (Gordon, 2018: 99).

Formal education – or, more exactly, a relative lack of it – is also 
considered a key source of the anti-system vote (Hobolt, 2016; 
Tyson and  Maniam, 2016; Antonucci et al., 2017; Becker et al., 
2017; Bonikowski, 2017; Essletzbichler et al., 2018; Gordon, 
2018; Lee et al., 2018; Rodrik, 2018). ‘Educational attainment 
is seen as a critical determinant of populist views, with those 
holding lower educational qualifications being more likely to be 
pro-Brexit’ (Lee et al., 2018: 151), populist or anti-European. 
Education is also frequently thought to be at the root of the 
localist/cosmopolitan divide that splits anti-establishment and 
mainstream party voters (Gordon, 2018: 110).

The third factor is generally income (Goodwin and Heath, 2016; 
Hobolt, 2016; Antonucci et al., 2017; Becker et al., 2017; Ford 
and Goodwin, 2017; Rodrik, 2018). The average anti-system 
and  anti-European  voter  is  not  only  older  and  less  well 
educated, but also poorer. Individuals on low incomes are much 
more likely to be Eurosceptic and to vote accordingly (Ford and 
Goodwin, 2014; Antonucci et al., 2017; Becker et al., 2017).

Frequently, age, education and income are lumped together to 
form the ‘holy trinity’ of the populist voter (Ford and Goodwin, 
2014; Hobolt, 2017; Becker et al., 2017). As summarised by Los 
et al. (2017) regarding Brexit, ‘citizens who were older, or lesser 
educated, or socially conservative or lower paid, were all more 
likely to vote leave, while those who voted remain tended to be 
on  average  more  highly  educated,  younger,  earning  higher 
incomes and more socially progressive’ (page 787).

Other individual factors are also present, albeit less prominently, 
in  analyses  of  the  individual  anti-establishment  and  anti-
European voter. Unemployment (Algan et al., 2017; Becker et al., 
2017; Los et al., 2017), inequality (Rodrik, 2018), and lack of 
geographical mobility (Lee et al., 2018) are deemed to drive the 
population towards anti-system voting and anti-Europeanism. 

Alongside the individual factors, geographical characteristics 
have also been identified as powerful drivers behind the advent 
of a geography of EU discontent. The very term ‘geography of 
discontent’ refers to a mix of local economic conditions in many 
rural areas and medium-sized and small cities (Los et al., 2017: 
788; see also Garretsen et al., 2018). It is also linked with what 
is known as the ‘great inversion’ (Moretti, 2012; Storper, 2013), 
that  is  ‘a  combination  of  job  loss,  declining  labour-force 
participation or declining per-capita income relative to national 
averages’ (Martin et al., 2018: 9). Many of these places have 
also been caught in or have moved towards what is known as 
a  middle-income  trap  (Iammarino  et  al.,  2018),  becoming 
increasingly incapable of sustaining economic growth as they 
are de facto not innovative enough to compete with the most 
productive regions of Europe and the world in high-skilled, high-
value-added manufacturing and services, and are too expensive 
to  compete  with  less  developed  regions  of  Europe  and 
emerging countries in low-cost manufacturing (Vandermotten 
et al., 1990). The resulting discontent may have led many of 
these areas to use the ballot box to ‘rebel against the feeling of 
being left behind; against the feeling of lacking opportunities 
and future prospects’ (Rodríguez-Pose, 2018: 190).

The  literature  has  highlighted  several  territorial  factors  as 
promoters  of  this  geography  of  discontent.  Migration  is 
probably chief among them as – together with rejection of 
European integration – it is at the core of many anti-system 
party manifestos (Goodwin and Heath, 2016; Hobolt, 2016; 
Becker et al., 2017; Ford and Goodwin, 2017; Goodwin and 
Milazzo, 2017; Lee et al., 2018; Rodrik, 2018).

According to Ford and Goodwin (2017), migration became the 
issue that articulated the whole anti-establishment and anti-EU 
movement in the UK. The emergence of immigration as a central 
controversy in the mid-2000s led to a ‘surge in support for 
a  new  political  challenger  that  swiftly  became  the  primary 
vehicle  for  public  opposition  to  EU  membership,  mass 
immigration,  ethnic  change,  and  the  socially  liberal  and 
cosmopolitan values that had come to dominate the political 
establishment’ (Ford and Goodwin, 2017: 20). The arrival of 
migrants in a given territory often served as the catalyst to 
channel the local population’s economic and cultural fears. Fears 
of economic insecurity related to greater competition, increases 

THE GEOGRAPHY OF EU DISCONTENT12

in trade, and the often unfounded but deep-rooted perceptions 
that  the  new  arrivals  could  take  jobs  away  from  the  locals 
(Guiso et al., 2017). Cultural fears were connected to a supposed 
dilution of local or national identity as a result of the arrival of 
Muslim or Roma immigrants (Rodrik, 2018) or with a dilution of 
local  distinctiveness  in  multiculturalism  (Hobolt,  2016). 
Immigration in Europe is increasingly seen by voters as ‘a source 
or  symbol  of  rapid  social  change  that  threatens  traditional 
identities and values’ (Ford and Goodwin, 2017: 21).

Shafique, 2016; Tyson and Maniam, 2016; Becker et al., 2017; 
Essletzbichler et al., 2018; Martin et al., 2018; Rodrik, 2018).  The 
post-2008 great recession is often mentioned in anti-European 
party manifestos (e.g. MoVimento 5 Stelle, 2018) as a driver of 
dissatisfaction.  Academic  research  has  also  focused  on  the 
consequences of the crisis for votes (e.g. Algan et al., 2017). 
Globalisation and trade competition are further justifications for 
the rise of the anti-system vote – although Becker et al. (2017) 
find little connection between these factors and the Brexit vote. 

Rurality  and  low  population  density  have  also  featured  in 
accounts of the rise of the populist vote, mainly in the USA 
(Rodden, 2016; Cramer, 2017), but also in Europe (Bonikowski, 
2017; Essletzbichler et al., 2018; Martin et al., 2018; Gordon, 
2018).  In  this  respect,  the  surfacing  of  a  geography  of 
discontent in the US Rust Belt and in the so-called flyover states 
was associated with the perception that rural voters were not 
getting  their  fair  share  of  respect,  attention  and  resources 
(Cramer, 2017). Anti-establishment voters have been found to 
cluster  in  rural  and  small-town  America,  whereas  pro-
establishment voters generally live in big cities (Rodden, 2016). 
Population density is key in this respect: the anti-system vote is 
closely related to relatively low population densities (Rodden, 
2016),  which  may  be  a  consequence  of  a  cosmopolitan/
traditional divide between cities and rural areas (Essletzbichler 
et al., 2018: 86). Geographical isolation has also attracted some 
attention (Lee et al., 2018).

Recently, there has been a stream of explanations focusing on 
economic decline (Johnson, 2015; Goodwin and Heath, 2016; 

Rodríguez-Pose (2018) has pushed this thesis further in his 
‘revenge of the places that don’t matter’. For him, the anti-
system  vote  is  a  response  to  long-term  economic  and 
industrial declines – starting well before the outbreak of the 
crisis – which have fuelled discontent among the inhabitants 
of traditional industrial hubs and formerly prosperous places 
experiencing  economic  decay  and  a  lack  of  opportunities, 
in  some  cases  for  decades.  ‘The  areas  left  behind,  those 
having witnessed long periods of decline, migration and brain 
drain, those that have seen better times and remember them 
with nostalgia, those that have been repeatedly told that the 
future  lays  elsewhere,  have  used  the  ballot  box  as  their 
weapon’  (Rodríguez-Pose,  2018:  200)  to  vent  their  anger 
against the establishment. According to him, ‘it has been […] 
the  places  that  don’t  matter,  not  the  “people  that  don’t 
matter”,  that  have  reacted’  (Rodríguez-Pose,  2018:  201). 
He  argues  that  once  long-term  economic  and  industrial 
decline have been taken into account, it is ‘often the relatively 
well-off, those in well-paid jobs or with pensions that heeded 
the call of populism’ (ibid, 2018: 201).

13

4.  PROVING THE 

THEORIES BEHIND 
THE GEOGRAPHY OF 
EU DISCONTENT

Most of the analyses feeding the theories about the rise of 
a geography of discontent and the anti-system voting are based 
either on theoretical essays or detailed analyses of one country 
and one election. This makes extracting and generalising what 
drives anti-system voting, in general, and anti-European voting, 
in particular, difficult. Do the factors behind the Brexit vote, for 
example, explain the rise of support for parties against European 
integration in Austria, Denmark, France, Italy or the Netherlands? 
Or are the drivers of anti-Europeanism intrinsically linked to 
country-specific characteristics?

In this paper, we provide the first assessment of the drivers 
behind  the  rise  in  votes  for  parties  opposed  to  European 
integration across all EU Member States, using a high level of 
granularity – covering more than 63 000 electoral districts in total.

The main aim of the analysis is to assess the extent to which 
long-term – economic, industrial, demographic and employment 
– decline is a key factor behind the vote for parties opposed to 
European  integration  in  the  most  recent  national  legislative 
elections, assuming that different types of decline may have 
different links to the anti-European vote. Following the thesis of 
the ‘revenge of the places that don’t matter’ (Rodríguez-Pose, 
2018), it is hypothesised that economic and industrial decline will 
have a greater bearing on determining the share of votes against 
European integration than demographic and employment decline.

We  will  also  examine  whether  the  role  of  other  factors 
identified by the literature as drivers of the anti-system voting 
– age, education, wealth, unemployment, migration, population 
density – remains unchanged once different types of economic 
decline are taken into consideration. 

4.1 THE MODEL 

In order to evaluate which factors drive the geography of EU 
discontent across the EU-28, the following model has been 
adopted:

AEVr,2013-2018  = α + β Economic & demographic changer,2000-2016 + γ Xr,t 

+ δ Share non CHES voter,2013-2018 + νc 
+εr,t 

(1)

previous  section,  these  include:  population  density,  rurality, 
regional wealth, employment rate, share of elderly population, 
education and net migration. The Share non CHES voter,2013-2018 
determines the share of votes going to parties not included in 
the  Chapel  Hill  Expert  Survey  (CHES).  Vc  captures  country-
specific effects, while εr,t denotes the error term.

4.2 DATA AND GEOGRAPHICAL UNITS

DATA

The dependent variable (AEVr,2013-2018) depicts the share of valid 
votes for parties opposed to European integration – as defined 
by the CHES – in the last national legislative election at the time 
of writing (the list and dates of elections covered in the analysis 
are included in Appendix 3), as defined by the CHES. Following 
the opinion of the political scientists involved in the CHES, the 
degree  of  opposition  of  a  party  to  European  integration  is 
classified  according  to  three  different  degrees  of  intensity: 
a party can be strongly, moderately, or somewhat opposed to 
the  European  project.  In  our  analysis,  we  group  the  parties 
according to their degree of opposition to European integration. 
The  first  group  includes  only  parties  strongly  opposed  to 
European integration. The base group combines parties that are 
strongly opposed or opposed to integration. The final group 
encompasses all parties – including those moderately opposed – 
which manifest some hostility to the European project.

The  total  number  of  votes  for  anti-European  parties  are 
gathered and expressed as a share of valid votes. For several 
EU countries, such data were retrieved from the CLEA dataset 
(Kollman et al., 2016). This dataset includes the latest election 
results at constituency level. Where constituencies are relatively 
small,  this  represents  a  detailed  spatial  breakdown  of  the 
results. Nevertheless, in several countries the constituencies are 
relatively  large.  Moreover,  for  several  recent  elections,  the 
results  had  yet  to  be  made  available  in  the  CLEA  dataset. 
In these cases, the election results were retrieved from official 
national sources. 

As not all parties in Europe are covered by the 2014 and 2017 
CHES, the share of parties not included in the CHES (Share non 
CHES voter,2013-2018) is introduced in the regression as a control 
variable. As seen in Figure 5, at 5 %, the share of votes for 
parties not included in the CHES is marginal, remaining below 
10 % in most countries. The main exception is Latvia, where it 
marginally exceeds 50 % of the vote, whereas in Croatia, Cyprus 
and Ireland it hovers around 20 %. Parties not included in the 
CHES are generally independent or parties that did not exist in 
2017, for the latest round of the CHES.

where (AEVr,2013-2018) denotes the share of the anti-European 
vote in the most recent national legislative election. Economic 
&  demographic  changer,2000-2016  represents  the  independent 
variable  of  interest:  economic,  industrial,  demographic  and 
employment change between 2000 and 2014 or between 2000 
and 2016. Xr,t is a vector of other variables that have been 
identified by the literature as leading to growth in the anti-
system  and  populist  votes.  Following  the  discussion  in  the 

Our dependent variable of interest, Economic & demographic 
changer,2000-2016,  represents  the  degree  of  economic  and 
demographic change in EU-28 electoral districts over the long 
term. Four different types of changes are considered. First is the 
average annual real growth of GDP per head at NUTS 3 and 
metropolitan region levels. Second, the difference in industrial 
employment share in total employment at NUTS-3 level depicts 
industrial change. Employment change is represented by the 

THE GEOGRAPHY OF EU DISCONTENT 
 
 
 
14

average annual percentage change in total employment at 
NUTS-3 level, while demographic change is covered by the 
annual average population growth at NUTS-3 level. The sources 
of all the variables are Eurostat and Cambridge Econometrics. 
They cover the period between 2000 and 2014 (in the case of 
GDP per capita, overall and industrial employment change) or 
2016 (in the case of population change).

Vector Xr,t includes a number of variables that are aggregated 
at  the  level  of  electoral  constituency  of  the  individual  and 
geographical factors identified in the theoretical section. Seven 
different variables are in this vector:

The  density/rurality  variables  and  distance-to-the-capital 
variables are calculated for every electoral constituency. All the 
other variables are sourced from Eurostat with the data collected 
at the most detailed geographical level available, i.e. NUTS-3 
regions. The only exception is the education proxy which is only 
available  at  NUTS-2  level.  The  descriptive  statistics  and 
correlations between variables as well as graphs indicating the 
correlation between the votes for parties (strongly) opposed to 
European integration and the main independent variables are 
provided in Appendix 4 and 5, respectively.

CONSTITUENCY BREAKDOWN

The geographical breakdown of the units of analysis was done 
at the most-detailed possible geographical scale. In order to 
deliver this geographical granularity, the CLEA dataset and 
electoral  data  from  national  sources  were  combined  with 
dedicated geospatial datasets4 representing the boundaries of 
the electoral districts or of the smallest units for which election 
result  data  could  be  retrieved.  Nevertheless,  specific 
constituency boundaries were not always readily available in 
geospatial datasets for the majority of EU Member States.

To fill these gaps, two strategies were followed. First, in the 
cases of Greece, Hungary and Malta, the constituency level was 
converted or aggregated to the NUTS-3 regional level, without 
substantial  losses  in  spatial  detail.  The  second  strategy 
comprised retrieving constituency boundaries from national 
sources or mapping the retrieved election results from national 
sources at a more detailed spatial level than constituencies. 
This method was successful for most countries. In some cases, 
constituencies or other election result reporting units needed to 
be grouped to ensure they matched with the available boundary 
datasets. Specific local administrative boundary datasets were 
used to match sub-constituency data for most of the countries5 
or to create constituency boundary datasets6.

The resulting breakdown includes a total of 63 417 geographi-
cal units in the EU-28, including municipalities or equivalent 
units in 13 countries, electoral constituencies in 10 countries, 
and NUTS-3 regions in the remaining 5 EU Member States. 
A table with the geographical units used, their number and 
average population by country is provided in Appendix 3.

1.   Density/rurality: We calculate the weighted population 

density for each constituency using the density 
(reference year 2011) of 1 km² grid cells. For each cell, 
density is multiplied by the population count. The 
products are summed by electoral district and divided 
by the total population of the district, providing 
a measure of spatial concentration. This indicator is 
complemented by an indicator of rurality, measuring the 
population in each grid cell located outside urban 
clusters. The rural population is expressed as a share of 
the total population of the spatial unit. Whereas the 
rural population share is 100 % or 0 % for many spatial 
units, the density indicator increases steadily from 
dispersed rural areas to villages, suburbs, towns and 
small, medium and large cities which makes it well 
suited for capturing the urban-rural continuum.
2.   Distance to the capital: The distance between each 
electoral constituency and its national capital is 
measured in km as the geodesic distance (as the crow 
flies) between the geographic centroid of the electoral 
district and the centroid of the national capital.

3.   Wealth: Regional wealth is proxied by the GDP per capita 

in purchasing power standards at regional and 
metropolitan region levels, expressed as an index of the 
EU-28 average for 2015.

4.   Employment rate: Employment rates are calculated 

using data from regional accounts, divided by 
population data for the 17-74 age range at regional and 
metropolitan region levels in 2015.

5.   Age: The share of population aged 65 and over in the 
total population in 2017 is used as a proxy for an 
ageing society. 

6.   Education: Education is depicted as the share of adults 

(25-64 years) with tertiary education in 2017.
7.   Net migration: Finally, the impact of migration is 

represented by the net migration rate, i.e. the difference 
between the number people moving to the region and 
the people moving out of the region between 2000 and 
2016 divided by the total population in 2000.

4. 

5. 

6. 

GRED = Georeferenced Electoral Districts Datasets

Data from the EuroGeographics EuroBoundaryMap local administrative units for Bulgaria, Spain, Croatia, Italy, Portugal, Poland, Finland, Sweden and Slovakia, 
and aggregated LAU2 data for Belgium. For the Netherlands, France and Austria recent LAU2 boundaries have been retrieved from official national sources as 
these boundaries are not yet available as part of the EuroBoundaryMap.

Ireland:  electoral  division  boundaries  combined  from  CSO  Ireland:  http://census.cso.ie/censusasp/saps/boundaries/eds_bound.htm  combined  with  http://www.
constituency-commission.ie/docs/constituencies_ireland.pdf;  Latvia:  EuroBoundaryMap  combined  with  data  from  https://www.cvk.lv/pub/public/30997.html; 
 Estonia, Slovenia, Lithuania and Luxembourg: combinations of NUTS-3 and/or LAU2 boundaries.

15

5. 

 WHAT DRIVES THE 
VOTES AGAINST EU 
INTEGRATION?

5.1. 

  LONG-TERM ECONOMIC DECLINE 
AND DIFFERENT CONTROLS

To assess which of the factors identified in the literature as 
potential drivers of anti-system votes is linked to anti-EU voting 
we perform an OLS regression using model (1). The base model 
considers only the votes for those parties that are strongly 
opposed or opposed to European integration, thereby leaving 
aside  those  with  a  moderate  degree  of  opposition  to  the 
European project. Relative economic decline – measured by the 
rate of change in GDP per capita between 2000 and 2014 – is 
used as the independent variable of interest. The results of the 
regressions are presented in Table 1.

The results confirm the main hypothesis. The coefficient of the 
rate of economic change is, regardless of the controls and of the 
inclusion or not of country-fixed effects, always negative and very 
strongly significant in all six regressions. Places that have experi-
enced long-term, above-average economic growth tend to vote 
less for parties opposed to European integration than those that 
have undergone relative economic decline (Table 1, regressions 

1 to 3). Once the economic trajectory of places is controlled for, 
population density is also a powerful driver of anti-system voting. 
Localities and regions with lower population density are more 
prone to support anti-European integration parties (regression 3) 
and, while rurality also has the expected impact (regression 4), 
its effect is trumped by that of density (regression 4). The remain-
ing control variables are introduced in regression 6. The results 
indicate that votes for parties (strongly) opposed to European 
integration are associated with the levels of education of the pop-
ulation living in a place, existing levels of employment, regional 
wealth and distance to the capital. Ageing and net migration pro-
vide significant coefficients with the expected impact, but with 
a  far  lower  significance  than  that  associated  with  economic 
decline, density, education and wealth (regression 6).

While the majority of the results seem to be in line with expecta-
tions based on the literature, there are a number of important 
surprises. First, once the economic trajectory of a place is con-
trolled for, it seems that the anti-system vote is in no way linked 
to where poor people live. Richer places vote more for parties 
opposing European integration than poorer ones. The fact is that 
a large share of the poor live in places that have been economi-
cally declining for quite some time. Second, ageing – which has 
featured prominently in individual accounts of the rise of pop-
ulism – seems to be a more marginal factor in the anti-establish-
ment vote than most other factors. And finally, regions and cities 
that are closer to the capital are marginally more likely to vote 
for parties opposed to European integration.

TABLE 1: Factors behind votes for parties (strongly) opposed to European integration

DEP. V.:  Share of vote for parties (strongly) 

opposed to European integration

(1)
OLS

(2)
OLS

(3)
OLS

(4)
OLS

(5)
OLS

(6)
OLS

Economic change

Population density

Rural

Distance to the capital

GDP per capita

Employment rate

Population 65 and over

Education

Net migration

Share of no CHES vote

Observations
R-squared
Country FE
Adjusted R-squared
F test

-4.64052***
(0.037)

-1.79273***
(0.064)

-1.79267***
(0.064)
-0.00032***
(0.000)

-1.78386***
(0.064)

0.00396***
(0.001)

-1.79072***
(0.063)
-0.00041***
(0.000)
-0.00671***
(0.001)

0.03327***
(0.006)

-0.23876***
(0.005)

-0.23802***
(0.005)

-0.23869***
(0.005)

-0.23793***
(0.005)

-2.10537***
(0.067)
-0.00043***
(0.000

-0.00103***
(0.000)
0.11045***
(0.004)
-0.14491***
(0.010)
0.05510***
(0.012)
-0.16978***
(0.009)
0.04181***
(0.010)
-0.22435***
(0.005)

63 307
0.12647
NO
0.126
8106

63 307
0.60906
YES
0.609
13195

63 307
0.61012
YES
0.610
12421

63 213
0.60955
YES
0.609
12789

63 213
0.61068
YES
0.610
11966

63 307
0.61962
YES
0.619
9757

Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

THE GEOGRAPHY OF EU DISCONTENT16

However, the OLS analysis presented in Table 1 says nothing 
about  the  direction  of  causality.  While  long-term  economic 
decline may lead to swelling the ranks of those voting for parties 
opposed to European integration, it may be the case that more 
votes for anti-system parties could undermine the economic 
prospects of a place. We do not believe that endogeneity is 
a serious problem in our analysis as the ascent of anti-system 
parties is a recent phenomenon in Europe and as, until recently, 
their brush with power been very limited, their capacity to affect 
regional economic performance in the past could be considered 
as almost negligible. However, and in order to dispel any poten-
tial endogeneity risks, we resort to an instrumental variable (IV) 
analysis. We instrument long-term economic change with fertil-
ity rates, as differences in fertility are connected to economic 
performance (low fertility is associated with lower economic 
growth), although there are no theoretical arguments that link 
high or low fertility to specific political options or to a more pro- 
or anti-European stance. Societies with low levels of fertility are 
not more or less likely to vote for parties critical of European 
integration. Econometrically, fertility is a very strong instrument 
and all tests satisfy the relevance criteria of IV analysis, with an 
extremely large first-stage F-statistic.  

The  results  of  the  IV  analysis  are  reported  in  Appendix  6; 
the results presented in Table 1 stand. If anything, economic 
decline is reinforced as a driver of votes for anti-European par-
ties. The most significant difference with the OLS analysis is 
that distance to the capital in regression 6 changes sign and 
becomes positive and significant.

As a further test of the robustness of the results presented in 
Table 1, the same regression is run including only the share of 
votes for parties opposing European integration as a percentage 
of the total number of votes for parties covered by the 2014 
and 2017 CHES. This reduces the number of observations by 
almost 10 000. The results, reported in Appendix 7, generally 
hold. The anti-European vote is mainly driven by economic 
decline, lower population density, employment opportunities, 
education and regional wealth (richer regions, when other fac-
tors are controlled, remain more anti-European). 

5.2. 

 CONSIDERING PARTIES WITH 
DIFFERENT DEGREES OF 
OPPOSITION TO EUROPEAN 
INTEGRATION

What happens when the share of parties moderately opposed 
to  European  integration  enters  into  the  equation?  Parties 
opposed to European integration vary in their degree of opposi-
tion to the EU project. In Table 2, we look at the relationship 
between the variables included in regression (6) in Table 1 and 
the share of votes for anti-European parties. First, only votes for 
the parties most strongly opposed to European integration are 
considered  (1).  Then,  those  strongly  opposed  and  opposed 
(1&2) and, finally, all parties that have voiced some opposition 
– even moderate – to the European project (1, 2&3).

Five  factors  emerge  as  the  most  constant  drivers  of  anti- 
system voting in Europe. Relative economic decline, lower levels 
of education, and fewer employment opportunities are all con-
nected to stronger anti-European votes – regardless of the level 
of opposition to European integration. The same applies for GDP 
per capita although, once again, the sign of the coefficient is 
positive and significant. Richer places in Europe are more likely 
to vote for parties opposed to European integration than poorer 
ones (Table 2). Distance to the capital displays a negative and 
significant coefficient in the three regressions: once other fac-
tors are considered, areas closer to the capital are more likely 
to support anti-European integration parties in national elec-
tions. However, these results must be considered in light of the 
volatility of this coefficient in the IV regression (Appendix 6) and 
the  analysis  including  only  parties  considered  in  the  CHES 
(Appendix 7).

Other factors that have been considered as drivers of the popu-
list  vote  show  a  lower  degree  of  consistency.  Density  only 
seems to be a catalyst for the anti-system vote when the votes 
for parties opposed or strongly opposed to European integration 
are taken into account. In contrast to the American literature, 
the impact of density (or the urban/rural divide) changes when 
moderately anti-European votes are included in the analysis 
(the coefficient becomes positive and moderately significant in 
regression 1, 2&3). European cities can also back moderate 
anti-European parties. Once this type of party is included in the 
analysis, anti-Europeanism ceases to be a rural phenomenon as 
urban dwellers are marginally, but significantly more likely to 
vote moderate anti-system parties than rural ones (Table 2). 

The coefficient for areas with a high share of elderly population 
is highly volatile. It is positive and significant in the base regres-
sion, but negative and significant when only the vote for the 
strongest anti-European parties is taken into account, and when 
the whole spectrum of opposition to European integration is 
included in the analysis.

Likewise, net migration does not seem to be as relevant an 
issue for the orientation of the vote as has been portrayed by 
populist parties. Zones with the highest recent inflows of people 
are less likely to vote anti-European. This does not apply when 
votes for parties strongly opposed and opposed to European 
integration (in this case, the coefficient becomes positive and 
significant) or when the whole spectrum of anti-European par-
ties (insignificant) are considered (Table 2).

17

TABLE 2:  Factors behind votes for parties opposed to European integration, considering different 

degrees of opposition

DEP. V.:  Share of vote for parties 

opposed to European integration

Strongly opposed (1)
OLS

Strongly opposed and 
opposed (1&2)
OLS

Strongly to moderately 
opposed (1, 2&3)
OLS

Economic change

Population density

Distance to the capital

GDP per capita

Employment rate

Population 65 and over

Education

Net migration

Share of no CHES vote

Observations
R-squared
Country FE
Adjusted R-squared
F test

-0.69266***
(0.041)
-0.00024***
(0.000)
-0.00265***
(0.000)
0.04176***
(0.002)
-0.16178***
(0.007)
-0.26127***
(0.008)
-0.18333***
(0.007)
-0.26622***
(0.008)
-0.09780***
(0.004)

63 307
0.67014
YES
0.670
5167

-2.10537***
(0.067)
-0.00043***
(0.000)
-0.00103***
(0.000)
0.11045***
(0.004)
-0.14491***
(0.010)
0.05510***
(0.012)
-0.16978***
(0.009)
0.04181***
(0.010)
-0.22435***
(0.005)

63 307
0.61962
YES
0.619
9757

Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

-0.55057***
(0.066)
0.00010***
(0.000)
-0.00219***
(0.000)
0.07000***
(0.004)
-0.26329***
(0.012)
-0.02545**
(0.012)
-0.08907***
(0.011)
-0.01563
(0.011)
-0.28251***
(0.006)

63 307
0.74615
YES
0.746
20420

THE GEOGRAPHY OF EU DISCONTENT18

5.3. 

 DIFFERENT TYPES OF ECONOMIC 
AND DEMOGRAPHIC CHANGE

The final analysis looks into the link between different types of 
economic and demographic change and the share of the vote 
for parties opposed and strongly opposed to European integra-
tion, our base regression. Four different types of change are 
analysed: three of an economic nature – change in GDP per 
capita, industrial employment share, and overall employment – 
alongside demographic changes. The regressions are run with 
the same control variables as in Table 1, regression 6. The coef-
ficients for the controls are not reported as they are in line with 
those presented in Table 1. The only significant changes con-
cern the regression for demographic change, where ageing 
regions and those with a higher inflow than outflow of people 
become less anti-European.

The results show that the rise in the anti-European vote is only 
associated with long-term economic and industrial decline. 
Places that have seen better times, often based on past indus-
trial power, are turning in very large numbers to parties opposed 
to European integration. Places with population and employ-
ment decline are, by contrast, less likely to vote for anti-Euro-
pean parties. 

TABLE 3:  Economic and demographic change and the rise of the anti-European vote

Economic change

Change in industrial employment share

Change in employment

Population change

Controls

Country FE

Observations
R-squared
Adjusted R-squared
F test

GDP per capita 
change
OLS

-2.10537***
(0.067)

YES

YES

63 307
0.61962
YES
0.619

Industrial 
change
OLS

Employment 
change
OLS

Demographic 
change
OLS

-0.31374*** 
(0.012)

YES

YES

63 307
0.61709
YES
0.617

0.50161***
(0.088)

YES

YES

63 307
0.61387
YES
0.614

0.65785***
(0.021)

YES

YES

63 307
0.61880
YES
0.619

Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

19

but have less of a role than that identified by US political scien-
tists (e.g. Rodden, 2016; Cramer, 2017). In Europe, once parties 
somewhat opposed to EU integration are included in the analy-
sis there is a reversal in the role of density, and urbanites 
appear more likely to vote anti-European than people living in 
less-dense suburban and rural places.

Distance to the capital varies according to the method used. 
If anything, areas farther away from national capitals tend to 
vote more for pro-European integration options.

Long-term economic and industrial decline emerge as two of 
the fundamental drivers of the anti-EU vote. As indicated by 
Gordon (2018:110), it has been long forecast that persistent 
territorial inequalities could lead to major political breakdown. 
However, more than the gap between rich and poor regions, it is 
the long-term economic and industrial trajectory of places that 
makes a difference in the anti-system vote. Corroborating the 
theory of the ‘places that don’t matter’, the long-term decline 
of  areas  that  have  seen  better  times,  that  have  often  had 
a grander industrial past, together with the economic stagna-
tion  of  places  hitting  a  middle-income  trap,  provide  fertile 
breeding  ground  for  brewing  both  anti-system  and  anti- 
European integration sentiment. This result vindicates the elec-
toral strategies of many anti-establishment parities which have 
strongly targeted their electoral campaigning on old industrial 
and economically declining areas (Goodwin and Heath, 2016; 
Shafique, 2016; Essletzbichler, 2018).

Not all types of decline, however, are behind the rise in the vote 
for parties hostile to European integration. It has been shown 
that population and employment decline have no role in the 
geography of EU discontent. One potential explanation for this 
is that – at least in terms of change in employment – govern-
ments may have already tried to address the sources of long-
term economic decline by promoting employment, mainly in the 
public and non-tradable sectors (Rodríguez-Pose, 2018), which 
can generate sheltered economies with limited capacity to fend 
for themselves in a more integrated economic environment 
(Fratesi and Rodríguez-Pose, 2016).

Overall, the results of the analysis are mainly in line with the 
Brexit vote account by Becker et al. (2017): a geography of dis-
content where immigration and trade play limited roles and 
which is fuelled primarily by low levels of education, low employ-
ment opportunities, and a historical dependence on manufactur-
ing. The main, and important, difference with Becker et al. (2017) 
is that once education, employment opportunities, and economic 
and industrial change are controlled for, richer places are more 
opposed to European integration than poorer ones.

6. DISCUSSION

The empirical analysis of anti-European integration voting across 
the  EU  has  confirmed  some  basic  beliefs  about  the  drivers 
behind the geography of EU discontent. Education is confirmed 
as an important factor for support (or lack of it) for European 
integration. Education has been prominent in past analyses of 
anti-establishment votes and is deemed to have played a crucial 
role not only in the Brexit referendum, but also in presidential 
elections in the USA and Austria (Essletzbichler, 2017). 

Lack of employment opportunities also rank high on the list of 
factors behind recent populist votes in Europe. As already noted 
by Algan et al. (2017), low levels of employment play a major 
role in the geography of EU discontent. However, and in contrast 
to the emphasis placed by Algan et al. (2017) on changes in 
unemployment, our results point towards low levels of employ-
ment as a boost for non-mainstream parties. 

But the similarities with the dominant narrative are as notewor-
thy as the differences revealed by the analysis. One such differ-
ence  relates  to  wealth.  In  the  past,  most  of  the  research 
highlighted  how  anti-system  voters  came  from  poor  back-
grounds. However, while we show that local wealth matters, the 
sign of the analysis does not match previous results. Once other 
factors – and especially long-term economic decline – are con-
trolled for, richer places in Europe display greater opposition to 
European integration. In other words, when faced with the same 
level of economic decline, regions with a higher GDP per head 
are more likely to vote for anti-EU options.

Moreover, the presence of an elderly population – one of the 
most frequent explanations for the rise of populism – does not 
result in a greater anti-EU vote. When the economic trajectory, 
the levels of education in the population, and the wealth of a 
place are taken into account, areas with a large share of the 
elderly vote less for both radical and moderate anti-EU parties. 
Furthermore,  net  migration,  rather  than  becoming  the  over-
whelming reason behind reactions against the system, as por-
trayed by anti-system parties, is only a marginal player (see also 
Becker et al., 2017; Colantone and Stanig, 2018). If anything, 
places with a relatively higher share of people inflow vote less for 
parties strongly opposed to European integration. Greater pres-
sure on public services, such as the health and education system, 
does not seem to have resulted in more support for parties 
opposed to the EU project. However, this finding warrants further 
attention to break down the types of migration and demographic 
composition, if any, that influence the anti-European vote. 

Purely geographical factors, which have usually attracted less 
attention, turn out to be robust drivers of anti-European voting. 
Density and rurality matter for this type of electoral behaviour, 

THE GEOGRAPHY OF EU DISCONTENTpolicies that go beyond fundamentally targeting – as has often 
been the case until now – either the more developed and often 
dynamic  large  cities  or  simply  the  least  developed  regions. 
There  is  an  urgent  need  at  all  geographical  scales  to  move 
beyond and complement policies focusing on the current situa-
tion – e.g. core cities or lagging-behind regions – to consider the 
dynamics of economic development. This entails thinking about 
viable development intervention to deal with long-term trajecto-
ries of low, no, or negative growth and provide solutions for those 
places suffering from industrial decline and brain drain, as well 
as those stuck in a middle-income trap. Moreover, the policies 
must  go  beyond  simple  compensatory  and/or  appeasement 
measures. This implies tapping into the often overlooked eco-
nomic potential most of these places have and providing real 
opportunities to tackle neglect and decline. Thus, place-sensitive 
policies (Iammarino et al., 2018) may be the best option for con-
fronting the economic decline, weak human resources, and low 
employment opportunities which are at the root of the geography 
of EU discontent. They may also represent the best method to 
both stem and reverse the rise of anti-establishment voting, 
which is threatening not only European integration but also the 
very economic, social and political stability which has overseen 
the longest period of relative peace and prosperity the continent 
has witnessed in its long history.

20

7.  CONCLUSIONS

This research is the first to shed light on what drives the votes 
against European integration across electoral districts in the whole 
of the EU, comparing votes for parties opposed to EU integration in 
the most recent national legislative election and controlling for dif-
ferent degrees of opposition to the European project. 

The results stress that the rise in votes for anti-EU parties is 
driven by specific combinations of socio-economic and geograph-
ical factors, and that the latter often shape the influence of the 
former at the ballot box. Hence, once long-term economic and 
industrial decline are addressed, it becomes difficult to assert 
that pro-/anti-system divides ‘cut across generational, educa-
tional and class lines’ (Goodwin & Heath, 2016: 331). Of these 
three divisions, only the educational divide remains. According to 
our analysis, the evidence that age and wealth matter for anti-EU 
voting cannot be sustained. In declining places, the old and the 
rich are more likely to vote pro-European. Although large shares 
of the elderly and the poor happen to live in economically and 
industrially declining places, across the whole of Europe they are 
not necessarily more hostile to European integration than the rest 
of the population.

Hence, anti-EU voting reflects long-term economic trajectories; 
once this is controlled for, only education, density, and lack of 
employment go along with expectations. 

Anti-EU voting is on the rise. Many governments and mainstream 
parties seem to be at a loss as to how to react to this phenome-
non. The research conducted in this article may offer some initial 
suggestions about how to address the issue. The results indicate 
that if Europe is to combat the rise of a geography of EU discon-
tent then fixing the so-called places that don’t matter is possibly 
one of the best ways to start. Responding to this emerging geog-
raphy of EU discontent requires addressing the territorial distress 
felt by those places that have been left behind and promoting 

21

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APPENDIX 1

Member State

AT

BE

BG

CY

CZ

DE

DK

EE

EL

ES

FI

FR

HR

HU

IE

IT

LT

LU

LV

MT

NL

PL

PT

RO

SE

SI

SK

UK

23

Elections included 

2002, 2006, 2008, 2013, 2017

2003, 2010, 2014

2001, 2005, 2009, 2014, 2017

2011, 2016

2002, 2006, 2010, 2013, 2017

2002, 2005, 2009, 2013, 2017

2001, 2005, 2007, 2011, 2015

2003, 2007, 2011, 2015

2000, 2004, 2009, 2012, 2015

2000, 2004, 2008, 2011, 2016

2003, 2007, 2011, 2015

2002, 2007, 2012, 2017

2011, 2016

2002, 2006, 2010, 2014

2002, 2007, 2011, 2016

2001, 2006, 2008, 2013, 2018

2000, 2004, 2008, 2012, 2016

2013

2002, 2006, 2011, 2014

2013, 2017

2002, 2006, 2010, 2012, 2017

2001, 2005, 2007, 2011, 2015

2002, 2005, 2009, 2011, 2015

2000, 2004, 2008, 2012, 2016

2002, 2006, 2010, 2014

2000, 2004, 2008, 2014

2002, 2006, 2010, 2012, 2016

2001, 2005, 2010, 2015

THE GEOGRAPHY OF EU DISCONTENT24

APPENDIX 2: Top 40 anti-European integration parties, according to the CHES 2014 and 2017 scores

Country

Party name

Score on European 
integration

Votes in the latest 
legislative election

FR

PL

NL

CZ

EL

EL

NL

UK

FR

SK

HU

SE

CZ

PL

BG

IT

FI

DE

DE

DK

IT

PT

AT

DK

CZ

IT

SE

EL

FR

IE

BE

FR

UK

BE

NL

IT

HU

NL

IE

HR

Front National

15 - Komitet Wyborczy Kongres Nowej Prawicy

Partij voor de Vrijheid

SPD

KKE - Kommounistiko Komma Elladas

Laikos Syndesmos - Chrysi Aygi

Forum voor Democratie

UK Independence Party

Debout la France

ĽS Naše Slovensko

Movement for a Better Hungary

Sweden Democrats

Svobodni

4 - Komitet Wyborczy KORWiN

ОБЕДИНЕНИ ПАТРИОТИ – НФСБ, АТАКА и ВМРО

Lega

PS

Nationaldemokratische Partei Deutschlands

Alternative für Deutschland

5905 Ø. The Red-Green Alliance

Fratelli d’Italia con Giorgia Meloni

PCP-PEV

FPÖ

5899 Ø. The Danish People’s Party

KSCM

Potere al popolo

Left Party

Anexartitoi Ellines - Ethniki Patriotiki Symmachia

La France Insoumise

Anti-Austerity Alliance - People Before Profit

Parti Populaire

Parti communiste français

Democratic Unionist Party

Vlaams Belang

Staatkundig Gereformeerde Partij

MoVimento 5 Stelle

Fidesz-KDNP

Socialistische Partij

Sinn Féin

Hrvatska Stranka Prava 1861 - HSP 1861

1.05

1.06

1.07

1.07

1.11

1.11

1.13

1.14

1.15

1.15

1.21

1.27

1.33

1.43

1.50

1.50

1.60

1.67

1.79

1.82

1.86

1.88

1.90

1.91

2.00

2.00

2.14

2.22

2.25

2.25

2.50

2.58

2.58

2.60

2.60

2.64

2.71

2.73

2.78

2.86

2 976 001

4 852

1 372 800

538 574

301 684

379 722

187 117

3 881 099

265 359

209 724

1 000 637

801 178

79 229

701 215

310 436

5 587 719

524 054

176 020

5 878 115

274 463

1 398 451

444 955

1 175 961

741 746

393 100

374 064

356 331

200 532

2 477 823

84 168

102 291

614 646

184 260

247 283

218 938

10 748 065

2 165 342

955 448

295 313

19 669

*  Wherever possible, the CHES assessment – 2014 or 2017 – was used that was closest in time to the election 

included in the analysis.

APPENDIX 3. Reference year of the election and the spatial breakdown of the analysis

25

Spatial units

Average 
 population*

Number of units

Number of 
NUTS3 
regions**

Member State

Election  
year

Type of units

Belgium

2014

Kantons/Cantons

Bulgaria

2017

Czech Republic

2017

LAU2

NUTS3

Denmark

Germany

Estonia

2015

2017

2015

Constituencies

Constituencies

NUTS3/LAU2 
(some grouped)

Ireland

2016

Constituencies

Greece

Spain

France

Croatia

Italy

Cyprus

Latvia

2015

2016

2017

2016

2018

2016

2014

Lithuania

2016

NUTS3 
(some grouped)

LAU2

Municipalities

LAU2

LAU2

Constituencies

Constituencies

Constituencies 
(some grouped)

Luxembourg

2013

Constituencies

Hungary

Malta

Netherlands

Austria

Poland

Portugal

Romania

Slovenia

Slovakia

Finland

Sweden

2014

2017

2017

2017

2015

2015

2016

2014

2016

2015

2014

NUTS3

NUTS3

LAU2

LAU2

LAU1

LAU2

Constituencies

Constituencies

LAU2

LAU2

LAU2

United Kingdom

2015

Constituencies

52,463

27,719

745,081

59,052 

268,011

128,291

112,821

215,720

5,628

1,822

7,506

7,389

139,053

415,921

62,784

127,907

496,719

200,434

42,793

3,957

101,289

3,383

478,818

254,453

1,845

16,554

32,277

95,904

209

265

14

92

299

10

40

48

8,207

35,416

556

7,960

6

5

48

4

20

2

388

2,122

380

3,092

42

8

2,927

317

290

650

44

28

14

11

402

5

8

52

59

101

21

110

1

6

10

1

20

2

40

35

72

25

42

12

8

19

21

173

1342

EU

7,874.66

63,417

* Reference year 2011 (calculation based on population data from the Eurostat 
** NUTS 2013 classification

THE GEOGRAPHY OF EU DISCONTENT26

APPENDIX 4:

Summary statistics

 N

 Mean

 St.Dev

 Min

 Max

 Median

 t-value

Share of vote for parties opposed to 
European integration

63 324

21.058

14.037

0

100

22.72

377.515

Economic change

63 399

Change in industrial employment share

63 399

Change in employment

63 399

.346

-3.83

.152

1.072

2.73

.669

-2.35

-18.8

-3.72

6.17

20.17

4.8

.21

81.367

-3.71

-353.24

.11

57.344

Population change

Population density

63 416

3.558

5.437

-25.79

42.47

3.13

164.772

63 416

701.216 1519.488

0 37651.54

223

116.213

Distance to the capital

63 416

330.775

379.368

.3

9398.96

299.87

219.569

GDP per capita

Employment rate

Population 65 and over

Education

Net migration

Share of no CHES vote

63 416

87.231

24.821

63 416

53.719

63 416

21.091

63 399

29.736

63 399

2.148

63 324

6.22

7.638

3.775

7.629

4.026

8.432

22.6

29.84

2.61

12.1

342.2

98.45

35.06

71.7

81.88

885.01

53.16 1771.155

21.02 1406.786

30.2

981.418

-15.48

34.45

1.61

134.311

0

100

3.79

185.626

27

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THE GEOGRAPHY OF EU DISCONTENT 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
28

APPENDIX 5:  Correlation between votes for parties (strongly) opposed to European integration and the main independent variables

Main variables of interest

Economic change

Industrial change

Demographic change

Employment change  

Other control variables

Density

Regional wealth

29

Age

Education 

THE GEOGRAPHY OF EU DISCONTENT30

APPENDIX 6: Factors behind the vote for parties (strongly) opposed to European integration (IV analysis)

DEP. V.:  Share of vote for parties 

(strongly) opposed to 
European integration

(1)
Instrumental 
variables 
(2SLS)

(2)
Instrumental 
variables 
(2SLS)

(3)
Instrumental 
variables 
(2SLS)

(4)
Instrumental 
variables 
(2SLS)

(5)
Instrumental 
variables 
(2SLS)

(6)
Instrumental 
variables 
(2SLS)

14.90202***
(0.468)

-5.48000***
(0.187)

-5.24839***
(0.185)
-0.00032***
(0.000)

-5.42782***
(0.187)

0.00324***
(0.001)

-5.31265***
(0.186)
-0.00042***
(0.000)
-0.00775***
(0.001)

-10.36761***
(0.275)
-0.00050***
(0.000)

Economic change

Population density

Rural

Distance to the capital

GDP per capita

Employment rate

Population 65 and over

Education

Net migration

Share of no CHES vote

0.10115***
(0.014)

-0.22613***
(0.004)

-0.22619***
(0.004)

-0.22632***
(0.004)

-0.22595***
(0.004)

Observations
R-squared
Country FE
Wald chi2

63 307

NO
1025

63 307
0.58824
YES
250029

63 307
0.59183
YES
253920

63 213
0.58921
YES
250927

63 213
0.59167
YES
257170

Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

0.00113***
(0.000)
0.13211***
(0.004)
0.04190***
(0.014)
0.17184***
(0.014)
-0.20079***
(0.010)
-0.03057**
(0.013)
-0.21854***
(0.005)

63 307
0.52861
YES
139420

31

APPENDIX 7. Results including only the vote for parties surveyed in the CHES

DEP. V.:  Share of vote for parties (strongly) 

opposed to European integration

(1)
OLS

(2)
OLS

(3)
OLS

(4)
OLS

(5)
OLS

(6)
OLS

Economic change

Population density

Rural

Distance to the capital

GDP per capita

Employment rate

Population 65 and over

Education

Net migration

Observations
R-squared
Country FE
Adjusted R-squared
F test

-4.69420***
(0.041)

-1.32396***
(0.0721)

-1.33059***
(0.072)
-0.00037***
(0.000)

-1.32130***
(0.072)

0.00574***
(0.001)

-1.33171***
(0.072)
-0.00045***
(0.000)
-0.00610***
(0.002)

53,619
0.11574
NO
0.116
12862

53,619
0.6340
YES

53,619
0.63527
YES
0.635
12586

53,546
0.63452
YES
0.634
13082

53,546
0.63575
YES
0.636
12086

Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1

-1.81961***
(0.076)
-0.00048***
(0.000)

0.00034
(0.000)
0.13240***
(0.004)
-0.15114***
(0.012)
0.11044***
(0.012)
-0.21137***
(0.010)
0.08216***
(0.013)
53,619
0.64620
YES
0.646
9502

THE GEOGRAPHY OF EU DISCONTENT32

33

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THE GEOGRAPHY OF EU DISCONTENTK
N
-
0
7
-
1
8
-
1
1
8
-
E
N
-
N

Any question, comment or contribution should be sent to the following 
address: REGIO-B1-PAPERS@ec.europa.eu

Editor: Lewis Dijkstra, European Commission, Regional policy
The texts of this publication do not bind the Commission

© European Union, 2018
Reuse is authorised provided the source is acknowledged.

ISBN: 978-92-79-98498-3 
doi:10.2776/61870