THE FAR-RIGHT POLITICAL PARTIES OF
THE EUROPEAN UNION IN THE CONTEXTS OF IMMIGRATION AND TERRORISM
Sage McCarty
Political Science 201: Political
Research Design
May 21, 2023
Link to Poster (Opens in New Tab)
Sections
- Abstract
- Introduction
- Literature Review
- Methodology
- Data Analysis and Findings
- Conclusions
- Bibliography
Abstract
Rhetoric on behalf of the far-right
linking immigration and terrorism provides an opportunity to analyze whether
instances of terrorist attacks or high levels of immigration, or both
phenomena, can be used as predictors for electoral support for the far-right. Correlations and linear relationships between
general variables of immigration and terrorism do not necessarily support
far-right rhetoric, as anti-immigrant rhetoric regarding terrorism may center
on certain demographic factors, such as the religion of perpetrators of
terrorist attacks
Immigration levels and far-right
success are simultaneously rising among European Union member countries during
a period in Europe marked by concerns over changing demographics and threats of
terrorism. This establishes a context
where possible relationships between far-right success, immigration levels, and
terrorism should receive attention. However,
analyses using correlations and linear regression reveal that a European Union
member country’s number of terrorist attacks, number of terrorism-related
arrests, and number of incoming migrants each year are not suitable predictors
for the percentage of the vote in a country that is cast for the far-right in
European Parliament elections during the following year.
Introduction
The far-right in Europe is gaining increasing success
in elections for the European Parliament in a period where the level of
immigration to European Union member countries, as an independent variable, consistently
has a significant, moderate, and positive linear relationship with the number
of terrorist attacks in those countries; despite this context, the success of
far-right parties in countries’ elections to for the European Parliament is not
adequately predicted through the use of independent variables pertaining to
immigration and terrorism. The first
section of this research paper, the literature review, explores existing
literature on voter behavior, the far-right, migration, and terrorism,
particularly as they pertain to European politics, for example, by providing
existing explanations for far-right electoral successes. The second section of this paper describes
the methodology used throughout the research process, whether related to
operational definitions of certain variables, the use of a translation tool to
overcome language barriers, the collection of data, statistical analysis, or
the establishment of what European parties are properly categorized as
far-right. The third section on data
analysis and findings explains statistical analyses on immigration, terrorism,
and far-right successes, along with the relationships of these phenomena with
each other; this section includes five parts that cover the topics of trends
regarding terrorism and immigration separately, potential relationships between
far-right successes and terrorism, potential relationships between far-right
successes and immigration, potential relationships between terrorism and
immigration, and the increase over time in the number of countries in the
European Union that had a far-right party win a notable percentage of the vote
in elections for the European Parliament.
The concluding section summarizes earlier findings, provides
recommendations for future research, and clarifies and expands on this
project’s findings.
Literature Review
The overall rise of the far-right in Europe, along with
relationships between elections, migration, terrorism, and other phenomena, have
received recent attention in political science literature and literature
surpassing disciplinary barriers. For
example, Larisa Doroshenko from the University of
Wisconsin—Madison analyzed ten European Union countries and their European
Parliament election results to conclude that consumption of “mass-market news
sources” increased voters’ tendencies to support far-right parties (2017, 3186,
3199). For example, voters were more
likely to support the United Kingdom Independence Party (UKIP) after using news
sources on the internet (3200). Cas Mudde from the University of Georgia and the University of
Oslo writes that far-right populist ideas entered mainstream politics in Europe,
to the point where even “[m]ainstream parties” openly
describe “immigration and multiculturalism as threats,” due to the recent
influx of refugees into the continent; this marked the end of the far-right’s
position on the fringes of European politics (2019, 32-33). Furthermore, Mudde
points out Hungary’s ruling Fidesz party as a conservative
party affected by the integration of far-right ideas into mainstream politics
(33). The findings of Doroshenko and Mudde represent
the potential for multiple factors—in these cases, the factors of changes in
communications and immigration—impact the success of far-right parties in
Europe. A study on the cultural and
economic variables contributing to far-right success in Europe also found that
poor economic conditions have a positive correlation with far-right success;
this study hypothesizes that far-right support may arise among “more affluent
regions” due to these poor economic conditions, while the far-right “subgroups”
of the “extremist right” and the “populist radical right” do not capitalize on
these conditions for the sake of their own political promotion to a great
extent (Georgiadou, Rori,
and Roumanias 2018, 103, 113). These subgroups have a further
differentiation between the extremist right and the populist radical right,
with the extremist right receiving more support in the face of poor economic
conditions, while the populist radical right receives more support in light of “cultural threats” tied to immigration (113). Therefore, the literature attests to
far-right successes having positive relationships with poor economic
conditions, immigration, and methods of communication.
Existing literature contains studies
focused on specific countries as well as studies spanning across continents that
analyze relationships between voter behavior, terrorism, and migration. A study by Marc Helbling
and Daniel Meierrieks involving multiple countries
across different continent states that immigration does not “unconditionally”
contribute to an increased number of instances of terrorism, while terrorism contributes
to views and legislation against immigration (2020, 977-978, 981). This study also establishes a connection
between terrorism and far-right electoral success by affirming “that terrorism…
benefits (right-wing) political parties that hold nativist views” (992). Meanwhile, a paper focused on Spanish
elections and terrorist attacks perpetrated by the Basque organization Euskadi Ta
Askatasuna (ETA) found that people are more inclined
to be involved in democratic processes after terrorist attacks, with attacks
against civilians influencing voter behavior this way more so than attacks
against military or law enforcement officers; as stated in the article, this
behavior echoes a theory that the feeling of anxiousness resulting from
terrorist attacks motivates involvement in politics. However, the study does not express that this
feeling of anxiousness contributes to a tendency to vote for parties with
certain ideological leanings, and the study instead affirms that terrorism does
not impact the voters’ support for parties that are already in office
Studies surrounding immigration’s
relationship to far-right electoral successes are mixed. A study focused on Finland found a negative relationship
between immigration and support for far-right parties, where increased
immigration negatively impacts the percentage of the vote in local elections
that goes to the Finns Party, a far-right party, “by 3.4 percentage points”
with every “1 percentage point increase in the share of foreign citizens in a
municipality;” instead, “1 percentage point” increases in immigrant populations
actually result in a shift of these “3.4 percentage points” to political parties
that favor immigration. Immigration also
contributes to an increased tendency to vote among people who support
immigration
Methodology
This project uses linear regression
to discover relationships between immigration, terrorism, and the success of
far-right parties in European Parliament elections. Variables derived from these concepts are
defined in line with the origins of the data.
For example, far-right success, a product of voter behavior, is defined
as the percentage of the vote in a country that was cast for a far-right party
(or far-right parties) in a given country in its election for the European
Parliament in a given year; the data for this variable is derived from the
European Parliament’s electoral returns
While working in the realm of
causation, data from the previous year are used to potentially explain data
from the following year; for example, data from 2018 regarding immigration and
terrorism are used to explain the percentage of the vote won by far-right
parties in countries in 2019.
Furthermore, data on far-right success, terrorist attacks, and
terrorism-related arrests were gathered manually. For instance, TE-SAT reports were used for
data on the number of terrorist attacks and arrests connected to terrorism in a
given EU country in a given year, and United Kingdom
figures are missing for the years 2020 through 2021 as a result of the United
Kingdom’s exit from the European Union (“Brexit”). Brexit likewise resulted in an absence of
immigration data for the United Kingdom in 2020 and 2021. Croatia is similarly also missing data
regarding immigration from 2010-2011 and terrorism in 2012. Data was not used from other sources for the purpose
of generating a normalized data set; other data sets may define immigration and
terrorist attacks differently—for example, through having different answers to
questions of whether migration between countries within the EU counts as
immigration, or whether a definition of a terrorist attack includes actions
that were prevented by law enforcement agencies—so only TE-SAT reports on
terrorism and Eurostat immigration were used.
Missing data were manually marked within Microsoft Excel files with
“-999.”
Furthermore, results from the
European Parliament’s elections were used due to the efficient and structured
natures of the frequency of elections (every five years) and simultaneous
elections within every EU member country.
Parties who supported candidates within these elections were defined as
far-right based variously on journal articles, news articles, and information
from websites. PolitPro,
an election information resource, was especially helpful in determining what
parties to consider as having a far-right position and in deciding what parties
to investigate for far-right tendencies
Data points were collected using
Microsoft Excel and analyzed using JASP, a statistical analysis tool. Classical correlation and linear regression
were primarily used to explore relationships between multiple variables, with
these relationships calculated through JASP.
Variations and averages within a single data set—such as within the
category of immigration—were calculated using Microsoft Excel and Google
Sheets.
Data Analysis and Findings
Part 1: Trends in Immigration and
Terrorism
As calculated through Microsoft
Excel, Eurostat migration data indicates a steady increase in immigration to EU
member countries from 2012 to 2019; the years 2010, 2011, 2020, and 2021 were
excluded from this analysis, despite the availability of data regarding these
years, to account for missing data for immigration to Croatia in 2010-2011 and
the United Kingdom from 2020-2021.
Despite this steady increase, there is a spike in 2015 with an average
of 172,948 migrants arriving in each EU member country. This spike may be linked to the Syrian
refugee crisis that began in 2014. After
this spike, the average level of immigration resumes to its general rise along
its trendline, as displayed through Google Sheets (shown below in Chart 4.1.1). There is a strong, positive, and linear
relationship between the year of immigration and the average total immigration
to each EU member country, as indicated by the regression coefficient (R2
value) of 0.797. Therefore, the average
level of immigration to European Union member countries steadily increased in a
strongly linear manner from 2012 to 2019.
Chart
4.1.1: Changes in average migration level to each EU member country per year,
2012-2019.
Furthermore, a longitudinal approach
to studying changes in the numbers of terrorist attacks each year reveals that,
in the years 2013 through 2019, there is only a weak, negative, and linear
relationship between the year and the number of terrorist attacks in each EU
member country, as indicated by the low regression coefficient (R2
value) of -0.24. This weak, negative,
and linear relationship indicates that, although the average number of
terrorist attacks in each European Union country tends to decline each year, the
decline in the average number of terrorist attacks per year in each European
Union member country is not consistent.
Also, the weakness of this relationship (R2 = -0.24) stands
out against the strength of the relationship between the year and the average
level of immigration to each European Union member country per year (R2
= 0.797). Immigration levels to each
European Union member country increase more consistently per year than the
average number of terrorist attacks in each member country. The below graph (Chart 4.1.2) utilizes TE-SAT
report data and excludes years prior to 2013 and after 2019 to account for the
lack of Croatian and United Kingdom data during those periods, respectively. Also, there are no clear spikes in the data
due to the linear relationship being weak.
Chart
4.1.2: Changes in average number of terrorist attacks in each EU member country
per year, 2012-2019.
In the years 2013 through 2019,
there is a moderate, positive, linear relationship between the number of
terrorism-related arrests in each EU member country per year and the year of
the arrests, as indicated by the regression coefficient (R2 value)
of 0.499. This regression coefficient
indicates that the increase in the number of terrorism-related arrests in each
European Union member country per year is somewhat consistent. Similar to the above
data on terrorist attacks, the moderate relationship leads to the absence of
clear spikes in the data. The below
graph (Chart 4.1.3) shows the change in the average number of terrorist attacks
in each EU member country per year from 2013 to 2019.
Chart
4.1.3: Changes in average number of terrorism-related arrests in each EU member
country per year, 2012-2019.
Therefore, the rate of the increase
in average immigration levels (R2 = 0.797) is higher than the rate
of the increase in the average number of terrorism-related arrests (R2
= 0.499) among EU member countries from 2013 to 2019. Although the average number of
terrorism-related arrests is steadily rising during these years, the average
number of terrorist attacks in EU member countries is inconsistently declining
(R2 = -0.24); however, the relationship between the year of the
attacks and the average number of terrorist attacks in EU member countries is
weak due to the low regression coefficient.
Part 2: Far-Right Success and
Terrorism
First
Model: Far-Right Successes in 2014 and Terrorism in 2013
Far-right successes in the European
Parliament’s elections are not adequately explained by data related to
immigration or terrorism; essentially, a country having a high level of
immigration or a high number of terrorist attacks in a year preceding elections
for the European Parliament do not strongly or significantly correlate, or have
a linear relationship, with a high percentage of the vote in those countries
going to a far-right party (or parties) in the next year’s elections for the
European Parliament. First examining
possible relationships between immigration in 2013 and far-right success in 2014
supports this conclusion, as there is only a weak correlation (Pearson’s r =
0.206) that is not statistically significant (p-value = 0.304) between these
variables. Regarding a linear
relationship between these two variables as calculated through linear
regression, with far-right success as the dependent variable and terrorist
attacks as the independent variable, there is a weak relationship (standardized
regression coefficient = 0.206) that is not statistically significant (p-value
= 0.304) between these two variables.
The weakness of the correlation and the linear relationship indicate
that the success of the far-right of different European Union member countries
in 2014 was only inconsistently related to high numbers of terrorist attacks in
the countries in 2013.
The R2 value for this
model is 0.042, and it only slightly improves to 0.043 when incorporating the
number of terrorism-related arrests in a country in 2013 into this model as an
independent variable; the low degree of improvement to this model may be caused
by the independent variable of the number of terrorism-related arrests in a
country in 2013, when used alone, only having a weak positive, and linear
relationship (standardized regression coefficient = 0.188) that is
insignificant (p-value = 0.439) with the percentage of the vote that was cast
for the far-right in a country in the 2014.
Even when used together, neither the number of terrorist attacks in a
country in 2013 nor the number of terrorism-related arrests in a country in
2013 are suitable predictors for the percentage of the vote that was cast in
that country that went to a far-right party (or parties) in the 2014 elections
for the European Parliament.
Second
Model: Far-Right Successes in 2019 and Terrorism in 2018
This pattern continues when
analyzing the next election for the European Parliament in 2019. There is only a weak correlation (Pearson’s r
= 0.182) between the number of terrorist attacks in each EU member country in
2018 and the percentage of the vote won by far-right parties in the 2019
elections for the European Parliament, and the relationship between these
variables is not significant (p-value = 0.364).
The linear relationship between these two variables, with far-right
success as the independent variable and terrorist attacks as the independent
variable, is positive and weak (standardized regression coefficient = 0.182). Also, this linear relationship is not
statistically significant (p-value = 0.364).
The weakness of both the
correlation and the linear relationship means that the success of countries’
far-right parties in 2014 was only inconsistently related to high numbers of
terrorist attacks in a country in 2013.
Incorporating the independent
variable of the number of terrorism-related arrests in each country in 2013
into this model only slightly improves the model’s R2 value from 0.053
to 0.054; this low degree of improvement may be caused by the presence of only
a weak positive and linear relationship (standardized regression coefficient =
0.182) that is insignificant (p-value = 0.364) between the dependent variable
of far-right success and the independent variable, when used alone, of the
number of terrorism-related arrests in a country. Therefore, reflecting the results of the
previous model on terrorism and voter behavior, neither the number of terrorist
attacks in a country in 2018, nor the number of terrorism-related arrests in a
country in 2018, are suitable predictors for the percentage of the vote in a
country that was cast for a far-right party (or parties) in the 2019 elections
for the European Parliament, even when these independent variables are used simultaneously
in the same model.
Findings
on Far-Right Success and Terrorism
Both the first and second model reveal
that neither the number of terrorist attacks in a European Union member country,
nor the number of terrorism-related arrests in the country, are appropriate
predictors for the percentage of the vote in a country that will be cast for the
far-right in the next year’s European Union elections, even when these
variables are used in combination. The
insignificance of the correlational and linear relationships involving the
variables on terrorism and far-right success indicate that observations of
correlational and linear relationships are properly explained by random chance. It is possible that the mistake of a Type II
error was made during the related calculations and analysis, meaning that,
although the null hypothesis that there is no relationship between terrorism
and far-right success was not rejected, this null hypothesis should actually have been rejected.
If this error was committed, the alternative hypothesis that there is a
positive linear relationship between terrorism and far-right success should
have received support in accordance with evidence in favor of this
hypothesis. Fixing this error would
require increasing the project’s sample size; however, the inclusion of only
European Union member countries through the focus on the European Parliament
prevents the expansion of the sample size to include more countries. The construction of models with future data,
or data from before 2013, may reveal a correlation or linear relationship
between terrorism and far-right success that is not present in these two
models. Based on these two models, the
numbers of terrorist attacks in European Union member countries and the numbers
of terrorism-related arrests in these countries are not accurate predictors for
the percentage of the vote that went to the far-right parties of these
countries during the following years’ elections for the European Parliament.
Part 3: Far-Right Success and
Immigration
First
Model: Far-Right Success in 2014 and Immigration in 2013
Regarding the relationship between the
percentage of the vote that was cast for the far-right in a country in 2014 and
the number of migrants entering a country in 2013, with far-right success as
the dependent variable and the level of immigration as the independent variable,
there is a moderately weak, positive, and linear relationship (standardized
regression coefficient = 0.346) that is not statistically significant (p-value
= 0.077) between these two variables. Similarly,
the correlation between far-right success in 2014 and immigration in 2013 is not
statistically significant (p-value = 0.077), and the correlation is positive
and moderately weak (Pearson’s r = 0.346).
The weakness of the correlation between these two variables and the weakness
of their positive linear relationship indicate that far-right success does not consistently
increase in accordance with increases in immigration. Due to the high p-values regarding
correlational and linear relationships, random chance adequately explains the
observations, and the null hypothesis that there is no relationship between
immigration in 2013 and far-right success in the election for the European
Parliament in 2014 should not be rejected.
Considering the high p-value of 0.077, the data does not support the
alternative hypothesis that the percentage of the vote won by the far-right of
different countries in 2013 is explained by the countries’ levels of immigration
in 2014.
Second
Model: Far-Right Success in 2019 and Immigration in 2018
A similar positive, moderately weak,
and linear relationship without statistical significance also exists in an
analysis of a possible relationship between different European Union countries’
levels of immigration in 2018 and the electoral success of the far-right in different
countries’ elections for the European Parliament in 2019. This relationship has a p-value of 0.305 and
a standardized regression coefficient of 0.205, with immigration as the
independent variable and far-right success as the dependent variable. The correlation between these two variables
has a correlation coefficient, or a Pearson’s r value, of 0.205 and a p-value
of 0.305. The weakness of the positive
correlational and linear relationships indicate that the
success of the far-right parties of different countries in European Parliament
elections in 2019 is only inconsistently related to a high level of immigration
into these countries in 2018.
Furthermore, the high p-values show that observations of these
correlational and linear relationships have a high likelihood of resulting from
random chance. Therefore, the level of
immigration to a European Union member country in 2018 is not an adequate predictor
for the percentage of the vote in that country that went to the far-right in
the country’s 2019 elections for the European Parliament.
Findings
on Far-Right Success and Immigration
Among the two relevant models that
were constructed, there is a moderately weak, positive, and linear relationship
between the level of immigration during a certain year and the percentage of
the vote in a country that was cast for the far-right in the election for the
European Parliament the next year.
However, this relationship is not statistically significant, so the
success of the far-right parties of certain countries in elections for the
European Parliament is not adequately explained by the previous year’s level of
immigration in those countries; instead, random chance properly explains the
observations of moderately weak, positive, and linear relationships within
these models. Analyses of correlations
between the same variables used in these models likewise reveals only
moderately weak and positive relationships.
The weakness of the correlational and linear relationships that were
analyzed in connection with these models reveals that the levels of immigration
to European Union member countries are only inconsistently related to the
success of these countries’ far-right parties in elections for the European
Parliament in the following years.
Although the null hypothesis that there is no relationship between
levels of immigration and the success of far-right parties should not be
rejected, a Type II error could have been committed. In this situation, this type of error means
that the null hypothesis should have been rejected and that evidence should
have been found that supports the alternative hypothesis that there are
positive correlational and linear relationships between the success of countries’
far-right parties in elections for the European Parliament, as the dependent
variable in the setting of linear regression, and the countries’ levels of
immigration during the following year, as the independent variable used in
linear regression. Fixing this error
would require increasing the project’s sample size; this is not possible given the
project’s current focus on countries the European Parliament, as an increase in
sample size would most likely include countries that are not members of the
European Union. The current focus on
connections between immigration and far-right success in elections for the
European Parliament reveals that a country’s level of immigration in one year is
not a suitable predictor for the percentage of the vote cast in that country
that went to the far-right in the election for the European Parliament in the
following year.
Part 4: Terrorism and Immigration
There is consistently a moderate,
positive, and linear relationship between the level of immigration to an EU
member country (independent variable) and the number of terrorist attacks in an
EU member country the following year (dependent variable), with the
standardized regression coefficients ranging between 0.393 in 2016 and 0.581in
2014 between 2012 and 2021 (Chart 4.4.1).
Although earlier calculations indicate that the average number of
terrorist attacks in each EU country decreased per year between 2013 and 2019,
while the average level of immigration to each EU country increased per year
between 2012 and 2019, there is still a moderate, positive, and linear
relationship—with a standardized regression coefficient ranging from 0.393 to
0.581—between the level of immigration during the previous year and the number
of terrorist attacks in EU member countries between 2012 and 2021. Also, out of the ten models generated for
this relationship to cover the years of terrorist attacks ranging from 2012 to
2021, all of the models show linear relationships that
are statistically significant when using a significance level of 0.05. This means that, by random chance, there is
less than a 5% chance of observing a moderate, positive, and linear
relationship between the level of immigration the previous year in an EU member
country (independent variable) and the number of terrorist attacks in an EU
member country between the years 2012 and 2021 (dependent variable), with these
relationships having standardized regression coefficients between 0.393 and
0.581. Due to these consistently low
p-values and the consistent appearance of moderate, positive, and linear
relationships, the null hypothesis that there is no relationship between
terrorism and immigration is rejected; instead, there is have evidence that
supports the alternative hypothesis that there is a positive, moderate, and
linear relationship between the number of terrorist attacks in an EU member
country and the level of immigration to that EU member country during the
previous year.
Chart
4.4.1: Changes in correlation coefficient for linear relationships between the
level of immigration to an EU member country in the previous year (independent
variable) and the number of terrorist attacks in that country during a
particular year (dependent variable), 2012-2021.
Part 5: Far-Right Parties Achieving
Notable Status
The percentage of European countries
who have a notable far-right party in regard to
European Parliamentary elections has gradually increased since 2009. Here, the idea of notable far-right parties
refers to far-right parties who received a percentage of the overall vote in
their country high enough for the percentage of the vote won by them to be
displayed on the European Parliament’s electoral return website, rather than
there being no far-right party involved in the election or the far-right party
(or parties) receiving a percentage of the vote in their country that was so
small that the result is relegated to the combined “Other parties” section in
the election results
Chart
4.5.1: Changes in the percentage of countries who had at least one far-right
party win a notable percentage of the country’s vote in the elections for the
European Parliament over the years 2009, 2014, and 2019.
Conclusions
While there is a moderate and significant linear
relationship between terrorism and immigration, there is no such relationship
between terrorism and far-right success or immigration and far-right success. The lack of significance among correlational
and linear relationships between terrorism and far-right success, along with
those between immigration and far-right success, demonstrates that variables
related to immigration and terrorism are not suitable predictors for the
percentage of the vote cast for the far-right in a country’s elections for the
European Parliament; this conclusion is further supported by how the weakness
of these correlational and linear relationships shows that variables related to
immigration and terrorism are only inconsistently connected to far-right
success in elections for the European Parliament. These conclusions indicate a possibility that
support for far-right parties in European Parliamentary elections may not
result from voters’ fears regarding multiculturalism or personal security. Furthermore, the relationship between
terrorism and immigration does not account for attributes such as the
perpetrators’ countries of origin or motives; it is inappropriate to state,
based on the linear relationship, that immigration leads to terrorism through
immigrants committing acts of terrorism.
Instead, acts of terrorism may be committed, especially by far-right
perpetrators, out of fears related to immigration.
Far-right sentiment is increasing
within Europe, as attested by the literature regarding this subject and by my
above finding on the gradual increase of the percentage of EU countries that
had a far-right party achieve a notable percentage of the vote in European
Parliamentary elections. While
immigration, terrorism, and far-right successes are simultaneously realities
for the European Union, the lack of consistency in associations between
immigration and far-right successes and between terrorism and far-right
successes leads to the conclusion that it is inappropriate to consider far-right
successes as byproducts of trends related to immigration and terrorism.
Further research should grant
attention to finding variables that contribute to increased electoral success
among the European Union’s far-right parties while using a wider range of tools
for statistical analysis. While this
project used correlations and linear regression to explore relationships
between variables, future research would benefit from the use of more diverse
methods of finding relationships between far-right success and its potential
predictors. Furthermore, future research
on connections between terrorism and voter behavior would benefit from an
exploration of how the scope and publicity of terrorist attacks impact voter
behavior; data used in this project does not allow for the number of people affected
by certain terrorist attacks or the scope of knowledge about certain attacks to
be factored into analyses on terrorism and far-right electoral successes. Also, although the recent success of
far-right parties in elections for the European Parliament may not receive
adequate explanation through variables centered on terrorism and immigration, the
inadequacy of these variables provides the insight that voters may support
far-right parties out of concerns related to other matters, such as economic
troubles or Euroscepticism, or that voters may be influenced to support
far-right parties based on more specific concepts that fall under terrorism and
immigration, such as the ideological motives for a majority of terrorist
attacks or the countries of origin of a majority of immigrants. Thus, the insight gained from these analyses on
the inadequacy of variables related to immigration and terrorism for explaining
far-right electoral successes has the potential to guide the focus of future
investigations into reasonings for the electoral successes of the European
Union’s far-right parties.
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