SOCIO-DEMOGRAPHIC FACTORS INFLUENCING ATTITUDE TOWARDS REFUGEES: AN ANALYSIS OF DATA FROM EUROPEAN SOCIAL SURVEY

Abstract

Globalization causes socio-demographic transformations and one of the most relevant is refugee crisis. In 2015, over 1 mil. people – refugees, displaced persons and other international migrants – have made their way to the EU. The EU has confronted the problem of illegal and extensive international migration. Recently it has been even more in the public focus of international organizations and separate countries as the influx of refugees has rapidly increased due to economic problems and wars in the Middle East. Most people have developed an attitude towards refugees and refugee crisis, as the topic has received a lot of publicity and media coverage. Therefore, a research concerning the socio-demographic factors influencing attitudes towards refugees is relevant offering an insight to the background of people's attitudes. Research results show that attitude towards refugees is highly associated with income level, country of residence, employment status and family structure but not with age, gender, education level and place of living. The results of research can be useful for understanding and perhaps solving many unwanted social problems, for example racism and discrimination based on religion or social status. Knowing the factors influencing the attitude formation eases the creation of multicultural society with a very diverse population in globalization context.

Full text

16th International Scientific Conference Globalization and Its Socio-Economic Consequences
University of Zilina, The Faculty of Operation and Economics of Transport and Communication, Department of
Economics 5th – 6th October 2016
286
SOCIO-DEMOGRAPHIC FACTORS
INFLUENCING ATTITUDE TOWARDS
REFUGEES: AN ANALYSIS OF DATA FROM
EUROPEAN SOCIAL SURVEY
Mindaugas Butkus1,a,*, Alma Maciulyte-Sniukiene2,b and Kristina
Matuzeviciute3,c
1Siauliai University Department of Economics, Visinskio str. 19, Siauliai, Lithuania
2Vilnius Gediminas Technical University Department of Business Technologies, Sauletekio av. 11,
Vilnius, Lithuania
3Siauliai University Department of Economics, Visinskio str. 19, Siauliai, Lithuania
amindaugo.butkaus@gmail.com, balma.m@splius.lt, cmatuzeviciute@gmail.com
*Corresponding author
Abstract. Globalization causes socio-demographic transformations and one of the most
relevant is refugee crisis. In 2015, over 1 mil. people – refugees, displaced persons and other
international migrants – have made their way to the EU. The EU has confronted the problem of
illegal and extensive international migration. Recently it has been even more in the public focus
of international organizations and separate countries as the influx of refugees has rapidly
increased due to economic problems and wars in the Middle East. Most people have developed
an attitude towards refugees and refugee crisis, as the topic has received a lot of publicity and
media coverage. Therefore, a research concerning the socio-demographic factors influencing
attitudes towards refugees is relevant offering an insight to the background of people’s attitudes.
Research results show that attitude towards refugees is highly associated with income level,
country of residence, employment status and family structure but not with age, gender,
education level and place of living. The results of research can be useful for understanding and
perhaps solving many unwanted social problems, for example racism and discrimination based
on religion or social status. Knowing the factors influencing the attitude formation eases the
creation of multicultural society with a very diverse population in globalization context.
Keywords: refugees, socio-demographic factors, globalization
JEL Classification: F60, F22, C21, Z13
1. Introduction
One of the key elements of globalization is migration which takes various forms: legal and
illegal, voluntary and forced. According to estimates of UN Refugee Agency, there are over 21
mils. Refugees in the world. More than 50 percent of them come from three countries: Somalia,
Afghanistan and Syria. Societies’ attitudes towards this problem influence government refugee
policies, so it is important to analyse what socio-demographic factors influence these attitudes.
The goal of the paper is to evaluate which socio-demographic factors influence attitudes
towards refugees in the EU. The rest of the paper is organized as follows: Section 2 presents
the literature review on determinants of attitudes towards refugees. Section 3 describes research

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variables, hypotheses and model. Section 4 presents the estimation results and summarises
research findings. The last section concludes the paper.
2. Determinants of attitudes towards refugees – literature review
Existing literature on attitude towards refugees is limited. In recent years there have been a
lot of discussions about refugee issue due to the increasing number of refugees in the EU and
other countries of the world, but not about factors influencing attitude towards this issue. It is
very important to identify attitude towards refugees, determine its causes and manage it because
negative attitude influences conflict in multicultural society.
Although immigrants and refugees do not belong to the same category, scientific literature
usually analyses attitudes towards migration with no special focus on refugees and in most cases
focuses on economic and non-economic factors influencing these attitudes. The main difference
of definitions “immigrant” and “refugee” is that migration is a voluntary decision and refugees
usually are forced to move from their country of origin. Despite this difference, this research
assumes that factors forming attitudes toward immigrants and refugees in most cases can be
similar.
There are different sociological theories which analyse factors influencing societies’
attitudes towards immigrants / refugees. Human capital theory analyses the influence of
education on attitude towards immigration / refugees. Theory states that higher level of
education causes higher tolerance, more support for immigrants / refugees, as people with
higher education do not need to compete with immigrants / refugees (mostly low educated) for
simpler and more abundant jobs (Mayda, 2006). It is also noted that the skill level of immigrants
does not change significantly the highly educated natives’ attitudes toward immigrants
(Rustenbach, 2010).
The theory of economic competition is applied at three levels: regional, national and
individual. At individual level, people perceive a threat from immigrants because of the
competition with local natives for jobs. At regional level, people with negative attitudes towards
immigrants live most likely in areas and districts where the main source of income is low-
skilled work and therefore there is harsh competition with immigrants for those jobs
(Rustenbach, 2010). Higher unemployment rate at national level leads to a more negative
attitude toward immigrants. The explanation of this effect can be similar to the aforementioned
“greater competition in the labour market makes natives feel threatened” (Paas & Halapuu,
2012).
The contact theory originated from Allport (l954) describes the impact of different
encounters and relations on the development of attitudes towards immigration. Fetzer (2011)
found that when contact with immigrants appears without any further knowledge or intimate
relations with the encountered immigrant, then the outcome was usually negative. People tend
to have a lot of prejudice towards things they do not know. Close relations with immigrants
create positive attitudes towards immigration and that extends to every type of immigrants.
Neighbourhood safety theory also emphasizes above mentioned fear of the uncertain and
new. Immigrants provide a lot of new and unknown to the communities, which enables the
natives to attribute many negative aspects of the community’s attitude to the immigrants
(Rustenbach, 2010). Earlier, some positive relations have been found between the unsafety of
a neighbourhood and negative attitude towards immigration (Chandler &Tsai, 2001).

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There are many factors which influence societies’ attitudes towards specific issues:
demographic, economic, social and cultural, political, geographical and etc. It is crucial to
understand how different factors influence societies’ opinion because that influences refugee
acceptance in destination country. Table 1 shows different factors influencing attitude towards
refugees and researches which analysed them in the context of migration.
Table 1: Factors influencing attitudes towards refugees
Determinants
Authors
Demographic
Gender, age, generational
status, marital status, race
Schweitzer et al., 2005; Mayda, 2006; Dustmann &
Preston, 2007; Berg, 2010; Facchini et al., 2011; Paas &
Halapuu, 2012; Murray & Marx, 2013; Bullard, 2015.
Social
Education, social class,
primary language, migration
experience
Schweitzer et al., 2005; Mayda, 2006; Dustmann &
Preston, 2007; Facchini et al., 2011; Gang et al., 2013;
Murray & Marx, 2013; Bullard, 2015.
Political
Political and political party
affiliation, religion
Chandler & Tsai, 2001; Dustmann & Preston, 2007;
Bullard, 2015.
Economic
Income, national pride, labour
market status, economic
security, fiscal cost
Mayda, 2006; Dustmann & Preston, 2007; Hainmueller &
Hiscox, 2007; Facchini & Mayda, 2009, 2012; Boeri, 2010;
Facchini et al., 2011; Paas & Halapuu, 2012; Gang et al.,
2013; Hatton, 2016.
Geographical
Location, town size
Finney& Peach, 2004
Source: authors’ contributions.
Researches explaining different factors influencing attitudes towards refugees/immigrants
are diverse. In general, most positive and tolerant attitudes are associated with youth, high
socio-economic status, high educational attainment and left wing political sympathies
(Hainmueller & Hiscox, 2007). Women seem generally more opposed to immigration than men
(Citrin et al., 1997). People with non-native or immigrant family members generally show more
positive attitudes toward immigrants than people from families without a recent history of
immigration (Mayda, 2006; Murray & Marx, 2013). People who are not born in the country
where they live, people who have ever belonged to a group discriminated against in the country
they live in, and people who have worked abroad have more tolerant attitudes towards
immigrants (Paas & Halapuu, 2012). In general, personal experience of migration (immigration,
emigration, and internal migration) can generate more tolerant and empathetic attitudes (Finney
& Peach, 2004). Individuals with right wing or conservative political ideologies, and those
evincing more national pride, are generally more likely to oppose immigration (Chandler &
Tsai, 2001). Other authors (Murray & Marx, 2013) find that political orientation had no effect
on respondents’ attitudes toward refugees. Highly-skilled individuals are more likely to adopt
tolerant attitudes towards immigration than low-skilled, and this effect is greater in richer
countries than in poorer countries, and in more equal countries than in more unequal ones. In
Western countries this is caused by western educational systems which are designed to increase
social tolerance (Gang et al., 2013). Chandler and Tsai (2001) point out that education fosters
tolerance, not just by increasing students’ knowledge of foreign cultures and raising levels of
critical thinking, but also by generating more diverse and cosmopolitan social networks.
Analysing economic determinants, it was found that individuals with less economic security
tend to have more intolerant attitudes towards refugees (Paas & Halapuu, 2012). A variety of
studies, particularly those by political scientists, argue that social and cultural values are more
important in shaping immigration opinion than economic considerations (Citrin et al., 1997;
Rustenbach, 2010; Manevska & Achterberg, 2013).
Results of research vary according to the specifics of country and period. It cannot be stated
whether it is negative or positive attitude towards refugees and there is a need for continuing

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research of society’s perceptions towards refugees. Furthermore, investigations should include
not only economic-social factors, but also demographic ones influencing public attitudes
towards refugees. This is proved in the present article.
3. Variables, hypotheses and model
The theory and results of empirical researches on immigration clearly show that the attitude
towards refugees is potentially related to many socio-economic factors. In accordance with a
previous part of the paper, having analysed various researches concerning this topic, in this
research binary logistic regression was chosen as the most suitable statistical tool for empirical
estimation of factors influencing attitude towards refugees and European Social Survey (ESS)
database as source of raw data. The attitude towards refugees was originally measured in
various Likert-type scales, ranging from 1-4 to 0-10 scales. To simplify interpretation, all the
above mentioned scales are re-encoded into only two values, using simple mathematical
division. In cases when scales had an uneven number of answer possibilities, the “leftover
value” in the neutral middle was counted as negative attitude. To this end, dependent variable,
describing European peoples’ attitude towards refugees, i.e. their positive or negative nature of
answers to questions regarding refugees, is encoded into binary form. Positive attitude was
described as value “1” and negative one as “0”.
The factors potentially influencing attitude towards refugees, i.e. independent variables in
the model, are chosen as follows: (i) Education level. It was originally categorized in ESS data
by ES-ISCED, a variant of ISCED (International Standard Classification of Education)
especially developed for working with ESS data. In this analysis four dummy variables are
assigned to the existing data: “basic education”, “high school diploma”, “vocational school
diploma” and “higher education”. “Primary education” is chosen as benchmark group. (ii)
Employment status consists of two dummy variables: “people without job looking for one” and
“people who are neither working nor looking for a job”. “Working people” is chosen as
benchmark group. (iii) Income of people in this research is described only by the subjective
opinion of the respondents, their answers coded into binary form: people who answered they
can manage (or even manage well) with their income – “0” and people who encounter
difficulties managing with their family’s income – “1”. Thus this dummy variable can be named
“insufficient income”. (iv) Gender coded into binary form: male – “0” and female – “1”. Thus
this dummy variable can be named “female”. (v) Marital status consists of three dummy
variables: “divorced”, “widowed” and “never married” people. “Married people” is chosen as
benchmark group. (vi) Children in family, like gender, are by essence dummy variable having
only two values: people either have children – “1” or they do not – “1”. Thus this dummy
variable can be named “children”. (vii) Religiosity is divided into two groups and encoded into
binary form: people who consider themselves religious – “1” and people not so – “0”. Thus this
dummy variable can be named “Religious”. (viii) Place of living conveniently reduced to binary
variable: people who live in cities encoded as “0” and people living in countryside as “1”. Thus
this dummy variable can be named “Countryside”. (ix) Nationality as variable was recorded
into two categories, both representing about half of the whole sample. Citizens of Northern and
Eastern European countries are encoded as “0”, people of Central and Western European
countries as “1”. Thus this dummy variable can be named “Central/Western Europe”. (x) Age
was grouped into four categories and three dummy variables are assigned to following groups
“from 21 to 40”, “from 41 to 60” and “61 and above”. “Up to 20” is chosen as benchmark
group. (xi) Neighbourhood safety was categorized and “feeling safe walking home after dark”

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assigned to “0” and the opposite of that to “1”. Thus this dummy variable can be named “lack
of safety”.
From theoretical background we can predict the possible impact of factor, i.e. independent
variables, on attitude towards refugees in the model. As many research papers emphasized, the
level of education is very important factor to consider. From that comes our first hypothesis:H1:
People with higher level of education possess more probability for positive attitude towards
refugees. From neighbourhood safety theory appears another testable hypothesis: H2: People
feeling safe will have more likely positive attitudes towards refugees. From theories about
natives’ financial situation two hypotheses can be deduced: H3: People whose work are more
likely to have positive attitudes towards refugees and H4: People who are satisfied with their
family’s financial situation are more likely to have positive attitudes towards refugees. For the
rest, following hypotheses are formulated: H5: People living in cities are more likely to have
positive attitudes towards refugees; H6: Females are more likely than males to have positive
attitudes towards refugees; H7: Younger people are more likely to have positive attitudes
towards refugees than older people; H8: Natives from Central and Western European countries
are more likely to have positive attitudes towards refugees than people from Eastern and
Northern Europe; H9: People who are married possess higher probability for positive attitude
than those never married, divorced or widowed; H10: People who consider themselves
religious are more likely to have positive attitude towards refugees than people who do not
consider themselves religious and H11: Families without children are more likely to have
positive attitudes towards refugees than families who have children.
The regression model for empirical estimations is composed as follows:


(1)
where P(Y) is a probability of occurrence of a positive attitude over negative attitude towards
refugees, as negative attitude in the model is the benchmark value. x1,…,x11 marks all eleven
independent variables, i.e. factors, in the model starting from education level. β1,…,β11 as usual
marks the regression coefficients, giving information how strongly and in which direction
independent variables respectively affect the odds ratio of the dependent variable.
4. Estimation results and discussion
On the whole ESS database consists of about 47 thousand respondents. Rather scare is data
about marital and work statuses (data about these factors is available for a bit more than 60%
of all questioned respondents). Incomplete data (nevertheless for some of variables we had data
from almost 99.9% of respondents) reduces sample size for our research and in our case it is
27598.In general, it appears that people in the EU have positive attitude towards refugees.
69.9% out of sample supports inflow of refugees into the EU, and think, that government should
be generous when assigning refugee statuses. Nevertheless, slightly more than half of
respondents think that refugees could make country’s crime problems worse.
Estimation results of binary logistic regression model linking factors with odds ratios of the
positive attitude towards refugees are presented in Table 2. Surprisingly education, gender,
religiosity, place of living, age and neighbourhood safety were estimated as statistically
insignificant factors not affecting attitude towards refugees at 95% confidence level. Because
of the globalization when people meet other cultures, change experience and traditions,

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familiarize with religions, society becomes more tolerant to different people. As it was proved
in previous research that attitude towards immigrants/refugees changes over time (see Facchini
et al., 2011). Thus we should reject hypotheses H1, H2, H5, H6, H7 and H10 because we do
not have clear statistical evidence, that factors corresponding to these hypotheses affect attitude
towards refugees.
Table 2: Estimation results of the model
Factors in the model
Estimated β
coefficient (B)
Standard
error
p-value
Exp(B)
95% C.I. for Exp(B)
Lower
Upper
Constant
1.659
0.631
0.009
5.254
Education level
0.428
Basic education
-0.058
0.317
0.854
0.943
0.507
1.755
High school diploma
-0,151
0.299
0.615
0.860
0.479
1.546
Vocational school diploma
-0.094
0.338
0.780
0.910
0.469
1.766
Higher education
0.190
0.321
0.555
1.209
0.644
2.270
Employment status
0.109
people without job looking for
one
0.340
0.415
0.413
1.405
0.623
3.170
people who are neither working
nor looking for a job
0.317
0.154
0.040
1.373
1.015
1.858
Insufficient income
-0.434
0.174
0.013
0.648
0.461
0.912
Female
0.129
0.141
0.360
1.138
0.863
1.501
Marital status
0.117
Divorced
-0.737
0.484
0.128
0.479
0.185
1.237
Widowed
-1.070
0.491
0.029
0.343
0.131
0.898
Never married
-0,642
0.494
0.194
0.526
0.200
1.358
Children
0.459
0.209
0.028
1.586
1.052
2.382
Religious
0.125
0.143
0.383
1.133
0.856
1.500
Countryside
-0.045
0.147
0.758
0.956
0.716
1.276
Central/Western Europe
-0.459
0.134
0.001
0.632
0.486
0.821
Age
0.505
from 21 to 40
-0.154
0.246
0.530
0.857
0.530
1.387
from 41 to 60
-0.224
0.293
0.446
0.800
0.450
1.421
61 and above
0.103
0.321
0.748
1.109
0.591
2.081
Lack of safety
-0.308
0.174
0.078
0.735
0.522
1.035
N
27598
-2 Log likelihood
1406.493
Pseudo R2
Cox&Snell
0.044
Negelkerke
0.065
Hosmer and Lemeshow test
χ2
12.022
p-value
0.150
Source: authors’ calculations.
We do not see statistically significant difference in attitude towards refugees between people
who work and people without job but looking for one. But we estimated that people who are
neither working nor looking for a job 1.4 times are more likely to have positive attitude towards
refugees than those who are recorded as active labour force. Thus we should reject hypothesis
H3, because we see impact in opposite direction than it was sensible from theoretical point of
view. This is contrary to theoretical explanation that individuals with less economic security

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have more intolerant attitude towards refugees. Active labour force has negative attitudes
because of the tougher competition in labour market and also wage decrease.
Confident feeling about household income affects the probability of positive attitude towards
refugees. People with insufficient income, according to model estimation, 1.6 (1/Exp(B)) times
are more likely to have negative attitude towards refugees than those who feel confident feeling
about household income. Thus we do not reject hypothesis H4.
Concerning the question of how generous should the government be supporting asylum
seeker flows and assigning refugee statuses, the people from Western and Central European
countries are 1.6 ((1/Exp(B)) times more not to agree with the statement compared with
Northern and Eastern European countries’ citizens. The explanation comes from the current
refugee crisis in the EU. In 2015, European countries received more than 1,3 million asylum
claims (Western countries receive majority of claims) and this caused different conflicts and
increase of crimes. Also we could state that Northern countries are more tolerant to refugees.
Eastern European countries are less developed so they are not very attractive to refugees and
do not face with this problem. Thus we should reject hypothesis H8, because natives from
Central and Western European countries seem less likely to have positive attitudes towards
refugees than people from Eastern and Northern Europe.
We do not see statistically significant difference in attitude towards refugees between
married, never married and divorced people. But we estimated that the widowed almost 3 times
are more likely to have negative attitude towards refugees than people with other marital
statuses. This factor has no theoretical background so it is needed for deeper research. Thus we
partly reject hypothesis H9, because we see difference in attitude towards refugees just between
married and widowed and no difference in attitudes between married and divorced, married and
never married.
People who have or ever had children, according to the model, 1.6 times are more likely to
have positive attitude towards refugees than those without. The value itself falls into rather wide
confidence interval of 95% confidence so the result should be interpreted with healthy
scepticism. Thus we have some statistical evidence to reject hypothesis H11 stating that people
without children have more probability of positive attitude towards refugees.
5. Conclusion
Society’s attitudes towards refugees are influenced by various factors: demographic,
economic, social and cultural, political, geographical and etc. These attitudes influence policy
towards refugees in destination countries. Thus research concerning the socio-demographic
factors influencing attitudes towards refugees is relevant offering an insight to the background
of people’s attitudes.
For this research binary logistic regression was chosen as the most suitable statistical tool
for empirical estimation of factors influencing attitude towards refugees and ESS database as
source of raw data. We developed 11 hypotheses about factors influencing attitudes towards
refugees in EU. As the research shows people who are neither working nor looking for a job,
feel confident about household income, originated from Central and Western European
countries, married and with children are more likely to have positive attitude towards refugees.
And in opposite – active labour force, people with insufficient income, living in Eastern and
Northern Europe countries, the widowed have negative attitude towards refugees.

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We can conclude that some of our findings were confirmed by previous research but some
results are controversial and there is a need for continuing research of society’s perceptions
towards this issue.
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