Download Realistic Group Conflict Theory and Economic Threats

Realistic Group Conflict Theory and Economic Threats: A Study of Anti-Foreign
Sentiments in 16 European Countries Using the European Social Survey Data
2002-2012
INTRODUCTION
The following paper aims to answer the question of whether deteriorating economic
conditions are likely to cause an increase in anti-immigrant prejudice in Europe. One of
the major findings in many of the cross-sectional studies is the fact that contextual
variables such as declining economic prosperity or high unemployment rates, coupled with
certain individual-level factors, have a positive effect on anti-immigrant attitudes in
Europe. More specifically, individuals with a particularly low socio-economic status are
most likely to experience the effects of environmental factors on their levels of prejudice
expression in relation to foreign nationals. These findings are most often explained in
relation to realistic group conflict theory (hereafter RGCT), which states that two groups
with divergent goals which compete over limited resources, be they tangible or intangible,
are likely to experience a feeling of threat from one another. These feelings of threat are
then likely to contribute to the increase in discriminatory attitudes and prejudice
expression between the two communities. RGCT has on many occasions been used to
explain why in times of relative economic decline, majority groups might develop negative
attitudes towards foreign workers. The perceived competition over material and nonmaterial resources such as jobs or financial opportunities is likely to result in feelings of
threat and fuel anti-immigration attitudes.
The major contribution of this paper comes from its distinction between subjective
(individual-level) and objective (contextual) ratings of economic performance. While
research on contextual determinants of prejudice is rife, little attention has so far been
given to subjective rating of economic conditions, which might not necessarily depend on
the real level of prosperity within the country. This distinction is particularly important
given that individual-level satisfaction with economy might have declined in many
European states post 2008 not as a result of deteriorating economic conditions, but the
rhetoric of crisis often employed by media and various right-wing parties. The following
study will attempt to determine whether real economic changes are a more reliable
predictor than subjective views of economic performance. It is crucial to note that the
following study gauges its dependent variable, the extent of prejudice toward immigrants,
by measuring anti-immigrant attitudes among respondents. It is assumed that those who
report that immigrants tend to case deteriorating economic, cultural and living conditions
are extremely likely to hold discriminatory views on foreign workers.
While many studies have previously shown that economic conditions might indeed
contribute to discriminatory attitudes, they usually either use data collected before the
2008 crisis, or are restricted to a single wave of major cross-sectional surveys such as the
European Social Survey (hereafter ESS). Apart from distinguishing between subjective and
contextual measures of economic performance, the following study further contributes to
the debate on the effects of contextual variables on prejudice expression. Unlike previous
studies, it utilizes all available waves of the ESS between 2002 and 2012 in order to
observe whether the extent of prejudice expression in Europe has changed as a result of
the 2008 economic crisis.
EXPLANATIONS OF PREJUDICE
Traditionally, the most influential theory accounting for prejudice expression is thought to
have been formulated by Gordon Allport (1954/79). He identified the formation of
individuals’ negative affects toward ethnic and cultural minorities as a result of their
insufficient exposure to what is located beyond their immediate social surroundings.
Allport (1954/79: 29-33) theorized that familiarity, fundamental to human survival,
becomes a value shared with those who happened to occupy our closest environment.
Over time, individuals become members of in-groups, or clusters of people ‘who can use
the term “we” with the same significance’ (Allport, 1954/79: 37). Besides the shared
value of familiarity, the subjects must possess a basic awareness of their in-group
membership (Tajfel, 1982: 2) This approach, termed the social contact theory, asserts
that insufficient socialization or lack of familiarity with members of foreign communities
will result in negative attitudes and generalizations of entire out-groups: cultures,
nations, creeds or classes. These antagonistic feelings can only be reduced by extensive,
controlled interaction between in-group and out-group members, resulting in the
reduction of social distance and increased tolerance (Allport, 1954/79; Pettigrew, 1998;
Pettigrew and Tropp, 2011). Although compelling, the theory fails to account for prejudice
and its absence in certain settings. Assuming the theory’s soundness, it renders all
members of extensive, homogenous groups such as nations with few cultural and ethnic
minorities invariably and equally prejudiced toward all out-groups; an assumption which is
clearly implausible. Secondly, the theory fails to explain why multiculturalism is often
thought to result in heightened ethnic tensions instead of contributing towards reduction
of conflict (Lentin and Titley, 2011). It has been widely reported that increase in
proportion of outside workers has a positive impact on the anti-immigrant sentiments
among the citizens of countries affected by the inflow of foreign labour.
REALISTIC GROUP CONFLICT THEORY
In order to account for these issues, the realistic conflict theory developed by Muzafer
Sherif (1966) has supplemented Allport’s (1954/79) argument with a third dimension:
competition for material or symbolic capital. Distinct groups will only stigmatize each
other if found in a direct, zero-sum contest over resources (Turner, 1975). Moreover,
according to the argument, prejudices serve a clear function of justifying the dominance
of the superior groups over the weaker one (Young-Bruehl, 1996: 50). In their Robber’s
Cave Experiment, Sherif et al. (1966) have shown competition to be a leading factor in
bias formation. They assembled two groups of young boys from similar white Protestant,
two-parent middle-class backgrounds that had not previously known each other and
divided them into two separate groups unaware of each other’s existence; after a period
of bonding, the groups were exposed to each other in a setting of various competitive
disciplines. Within days, derogatory terms and songs relating to competitors had been
invented and desire of segregation expressed, along with raiding of the other group’s
property, by which goods were damaged and stolen (Sherif et al., 1966: 96-113). Various
other experimental studies further confirmed that competition tends to increase
intergroup hostilities (Sherif, White & Harvey, 1955; Rabble and Horwitz, 1969; Blake and
Mouton, 1962).
RGCT AND ANTI-IMMIGRANT ATTITUDES
Realistic group conflict theory is one of the most widely used explanations for the high
prevalence of anti-immigrant attitudes. RGCT assumes that groups which find themselves
locked in a zero-sum contest over resources will tend to experience a high degree of
threat, and that the threat is then likely to result in stigmatization and development of
discriminatory practices and prejudice expression among the contesting groups (Sherif,
1966; Turner, 1975). This competition might concern material resources, such as
employment or housing opportunities, as well as less tangible capital such as power,
values or social status. The threat of losing vital resources results in negative attitudes
towards competitors. It follows that worsening economic conditions, leading to higher
rates of unemployment, are likely to result in hostilities between groups which directly
compete over jobs and material resources.
Furthermore, prejudice might also serve as a means of preserving the social position of
dominant groups against what they consider as a threat to their current status. Individual
interests of the in-group members, although relevant, are not as crucial as the privileges
of the group as a whole (Bobo, 1988). It has been shown that dominant group members
whose interests are not directly or immediately threatened in the competition are as
likely as others to develop discriminatory attitudes toward group rivals (Sears and Funk,
1991). As a result, Quillan (1995) has theorized about the importance of contextual factors
in accounting for individual prejudice expression, stressing the importance of economic
conditions such as unemployment rates and GDP per capita in explaining the rise of antiforeign sentiments in Europe. Although deteriorating economic conditions do not affect
the entire population of a country, they are nonetheless likely to result in increased antiimmigrant prejudice. The majority will be more concerned with the threat foreign workers
pose to the group as a whole, rather than to its individual members. For this reason,
individual-level variations are not enough to satisfactorily explain the prevalence of antiforeign prejudice. Contextual variables such as economic conditions need to be considered
if discriminatory behaviour is to be fully accounted for.
PREVIOUS RESEARCH
Research on context-related determinants of prejudice expression has become widespread
in recent years (Coenders, 2001; Semyanov et al., 2006; Sides and Citrin, 2007; Semyanov
et al., 2008). The rising of anti-immigrant sentiment across Europe in connection with the
2008 economic crisis has led to renewed interest in how economic conditions might affect
the public’s attitude toward foreign workers (Mueleman and De Witte, 2014). Although
Quillian’s (1995) research has found that contextual variables indeed tend to increase
anti-foreign attitudes, the relationship between economic conditions and discriminatory
opinions has since been largely contested. While some research confirms the effects of
economic conditions on negative perceptions of immigrants (Coenders, 2001; Semyanov et
al., 2006; Semyanov et al., 2008), others find little or no effect when
including
contextual variables in their models (Strabac and Listhaug, 2008; Sides and Citrin, 2007).
However, given the recent rise in unemployment and economic hardship following the
2008 Eurozone crisis, it is likely that these effects will become more prominent in
multilevel analysis. The release of the sixth wave of European Social Survey data from
2012 should allow for a more detailed investigation into how economic conditions might
have affected prejudice expression in Europe. Although a recent study by Billiet,
Mueleman and De Witte (2014) has tested the assumptions of RGCT by analysing the 2012
edition of the ESS, their research has been limited to one wave only, making it difficult to
test for change in immigrant perception before and after the 2008 economic crisis. The
following paper will investigate all six waves of the ESS data, including both individual and
contextual variables.
Furthermore, although contextual variables are likely to have a significant effect on antiimmigrant prejudice, it is crucial to note that individual perception of economic
performance is likely to be as important as unemployment levels or GDP growth. While to
a large degree the subjective views of economic conditions might be correlated with the
environmental factors, it is likely that individuals might change their views depending on
the information they are receiving from their immediate surroundings. The crisis rhetoric,
prevalent in many European countries after the 2008 financial crash, has been adopted by
both the media and right-wing parties and had likely changed the way individuals perceive
their state’s economic performance. A further discussion of subjective ratings of economy
and how it might affect prejudice expression is included in the methods section.
In conclusion, the following study contributes to the body of quantitative literature on the
RGCT in three ways. Firstly, it employs a double measure of economic performance and
compares its effects on anti-foreign attitudes. Secondly, it employs all six waves of the
ESS in order to investigate whether prejudice expression has changed as a result of the
2008 crisis. Finally, through employing all six waves of the ESS, the paper contributes
significantly to the debate on whether contextual economic variables do indeed affect
prejudice expression. The sudden spike in unemployment and stagnating economic growth
observed in many European countries after the 2008 financial crisis are the first
opportunity to fully investigate whether sudden changes in economic prosperity does
indeed affect anti-immigrant attitudes.
METHODS
The data for the current study has been obtained from all six waves of the European Social
Survey conducted every two years between 2002 and 2012. All individuals subjected to the
survey have been selected through random probability sampling and include all persons
aged 15 and above, regardless of their nationality, language or citizenship. In order to
capture the opinion of the majority group within the country, the sample has been
restricted to citizens of a given country only. Furthermore, given that the present study is
primarily concerned with measuring attitudes towards immigrants, respondents who have
identified themselves as foreign workers have also been dropped from the sample 1 . In
order to collect data from all waves between 2002 and 2012, the number of countries
1
In order to be identified as foreign nationals, respondents had to answer positively to a question
regarding potential prejudice against a group they consider themselves to be a member (“Would
you describe yourself as being a member of a group that is discriminated against in this country?”)
and provide with “nationality” as a reason for discrimination (“On what grounds is your group
discriminated against?”)
available for analysis has been dropped to 16, due to limited ESS coverage. Allowing for
other modifications such as elimination of missing values and restricting the age group to
15-90 years of age, the sample size has further decreased to 154,736 respondents.
MEASURING PERCEIVED THREAT
Three items from the ESS survey have been used to construct a tolerance scale for this
study: the perceived impact of immigrants on a state’s economic conditions (“Would you
say it is generally bad or good for [country]’s economy that people come to live here from
other countries?”); the perceived impact of immigrants on a state’s culture (“And, using
this card, would you say that [country]’s cultural life is generally undermined or enriched
by people coming to live here from other countries?”); and the overall impact of
immigration on the living conditions within a state (“Is [country] made a worse or a better
place to live by people coming to live here from other countries?”). The remaining items
referring to immigration, such as whether more or less immigrants ought to be allowed in
the country, have been left out from the scale, given that answers to these questions
were likely to have been highly dependent on the perceived impact of foreign workers on
the state’s economy, culture and living conditions. All three items have been shown to
measure the same concept through use of confirmatory factor analysis and have been
previously used by a number of studies concerned with measuring perceived threat from
immigrants (Billiet, Mueleman and De Witte, 2014; Schneider, 2008; Billiet and Philippens,
2004; Coenders et al., 2005). The scale is highly reliable, with Cronbach’s alpha = 0.8366,
a very high score considering how few items have been used to construct the
measurement. The lower the score on the 11 point item, the more prejudiced the
respondent is considered to be. Figure 1 presents the average scores for all 16 countries
on the tolerance scale, with results ranging from 4.36 for Hungary to 6.26 for Sweden. The
overall mean score on the scale for all countries is 5.27.
Figure 1. Mean tolerance scores, by country
INDIVIDUAL LEVEL VARIABLES
Following previous studies, the paper uses socio-economic indicators as individual-level
predictor variables in the model. It is assumed that those with a lower socio-economic
status (measured by highest educational achievement and net household income levels)
will feel more vulnerable and therefore more threatened by foreign workers who they
might perceive as potential competitors. Since resource competition tends to be much
higher in low-status occupations which do not pay well and require little to no formal
education, and immigrants, on average, tend to compete with the majority group
members for these positions, these members of the population might feel more
threatened by immigrants than others (Schneider, 2008: 55) Moreover, those with medium
and higher incomes are more likely to express positive views on immigration due to having
more potential for developing support systems in case of unexpected or prolonged periods
of unemployment. For this reason it is hypothesised that individuals with higher
educational and income levels will express more favourable views of foreign workers’
impact on their country, culture and economy.
There are also demographic variables such as age and gender that are expected to have a
significant impact on the tolerance scale scores. Previous studies suggest that
discriminatory attitudes are more pronounced among women and older people (Semyanov
et al. 2002; Semyanov et al., 2008). Since men tend to have a better access to education,
an interaction effect for male gender and tertiary education has been included in the
model. Due to the high number of younger respondents in the dataset, an interaction
between age and tertiary education has also been taken into account.
Given that group threat theory assumes that those who feel economically vulnerable or
disadvantaged tend to have a higher perception of threat from foreign workers, a dummy
employment variable has been included in the analysis. Finally, those who have
experienced potential economic hardship due to unemployment in the past (“Have you
ever been unemployed and seeking work for a period of more than three months?”),
individuals with history of unemployment, are also expected to be significantly more likely
to score lower on the 11 point tolerance scale. An interaction between being currently
unemployed and having been unemployed for at least 3 months in the past has also been
included, as it suggests a more consistent history of economic hardship.
CHANGES IN PREJUDICE EXPRESSION BETWEEN 2002 AND 2012
Firstly, utilizing descriptive statistics, the study will investigate whether the level of antiimmigrant prejudice has increased or decreased over time. Since the economic conditions
in most European countries have deteriorated or their economic growth has slowed down,
it is assumed that, in suit with RGCT, the levels of prejudice have increased as a result of
rising competition over resources between the majority group and the out-group (the
foreign workers). Therefore:
H1: The respondents are more likely to score lower on the tolerance scale in the waves
four (2008), five (2010) and six (2012) then in the first three waves (2002, 2004, 2006).
INDIVIDUAL PERCEPTION OF THE CURRENT STATE OF ECONOMY
RGCT predicts that individuals are likely to express prejudice regardless of whether their
economic position is immediately threatened or not. It is therefore crucial to include an
individual level variable which could reflect the feelings of the majority group about
current economic conditions. For this reason, subjective assessment of the state’s current
economic performance will be included in the model. It is important for two reasons.
Firstly, individuals dissatisfied with the state of economy in their country, regardless of its
actual performance, are more likely to feel threatened by immigrants, even if their wellbeing is not directly threatened. Perception of poor economic performance might reflect
the perception of hardship faced by other members of the group. The awareness of
economic difficulties is likely to increase the perceived threat the immigrants might pose
to the majority group.
Secondly, the measure is likely to have bearing on individual-level differences in prejudice
expression. More specifically, low economic satisfaction might be due to some subjective
experience of hardship which has not been captured by employment status or income
variables. Given that economic satisfaction is likely to be partially influenced by the
actual economic condition within the state, it will be allowed to vary both at the
individual and state level in the model. The economic satisfaction variable is normally
distributed, and is a scale from 0 to 10, where 0 indicates the lowest level of satisfaction,
and 10 the highest level of satisfaction (see table 1 in appendix 1 for more details).
H2: The higher the respondents’ place themselves on the economic satisfaction scale, the
more likely they are to score higher on the tolerance scale.
CONTEXTUAL VARIABLES
As stated by Quillian (1995: 591), it is expected that the weather the country, the lower
the amount of individuals who find themselves in direct conflict over scarce resources
with the foreign workers. The level of competition is likely to have impact on the overall
perception of immigrants among the in-group members. High GDP per capita and low
unemployment rates are expected to have a negative impact on discriminatory attitudes
across all countries. Average rates for both economic performance indicators have been
calculated to make sure that small variations in either unemployment rates or GDP per
capita do not influence the results. The averages are for three years prior to the ESS data
being collected. For example, in order to calculate the mean of unemployment for the
first wave of the ESS (2002), the mean GDP per capita (in $1000) and mean unemployment
rate (%) has been calculated from years 2000, 2001 and 2002. It is expected that:
H3: The higher the mean GDP per capita ($1000) in a country, the higher the scores on
the tolerance scale in the county,
and:
H4: The higher the mean rate of unemployment (%) in a country, the lower the scores on
the tolerance scale in the country.
ANALYSIS AND FINDINGS
Figure 2 demonstrates the changes in mean tolerance score by ESS wave. While tolerance
towards immigrants is highest during the fourth wave (2008), it drops in the subsequent
wave, and rises again to similar levels in wave 6 (2012). However significant, this variation
does not seem to be large enough to be attributed to the 2008 economic crisis, as a
similar drop can be observed between wave one (2002) and wave 2 (2004). Contrary to the
predictions formed in hypothesis 1, the graph suggests an upward trend in tolerance
scores.
Figure 2. Change in mean tolerance score by ESS wave
Figure 3 demonstrates the changes in tolerance score distribution before and after the
2008 crisis. While a certain level of variation is obvious, the results are not conclusive. It
is clear from the plot that there were major differences in respondents’ attitudes toward
foreign workers depending on the questionnaire wave. In 2002, the respondents seemed to
have a much more unified view of the impact immigrants have upon their country, with
over 25% of people scoring below 5 on the tolerance scale. The lower the score on the
tolerance scale is, the less favourable the view of foreign workers in general. In 2004,
negative attitudes toward immigrants have become more prevalent, with almost 50% of all
respondents scoring 5 or below on the scale. Furthermore, the minimum observation has
decreased relative to the first wave, indicating a polarizing trend in anti-immigrant
attitudes. In the third wave (2006) this trend seems to be even more prominent, with
greater amount of people reporting more extreme views on immigrants. While the
maximum and minimum values remain relatively similar in the 2008 wave, the 2010 wave
indicates that more and more respondents express positive views of immigrants relative to
previous waves. The 2012 wave has seen the median tolerance score reaching its highest
point since the ESS begun in 2002, indicating that over 50% of respondents held a positive
opinion on the impact of foreign workers on their country. These results are somewhat
surprising. It was expected that anti-immigrant prejudice would increase, rather than
decrease, as a result of the 2008 crisis. On the contrary, people seem to have gained a
more positive outlook on foreign workers with time. These results contradict the
assumptions of RGCT. According to its premises, deteriorating or stagnating economic
conditions, which have been observed in most of European states after the 2008 economic
crisis, should have a positive effect on the rise in prejudice as a result of direct economic
competition between the majority and minority groups. These initial results suggest that
the social contact theory, discussed in the initial section of this paper, is a more plausible
explanation of the prevalence of prejudice. The spike in migration might have contributed
to the increase in socialization between the groups and decreased, rather than increased,
the level of prejudice expression among the respondents.
6.5
Figure 3. Changes in tolerance scale score distribution by ESS wave
Sweden
4
4.5
5
5.5
6
15 Sweden
Sweden
2002
2004
2006
2008
2010
2012
ESS wave
Source: EVS 2002-2012
Upon estimating the null model, the interclass correlation coefficient of 0.07 has
confirmed that a considerable difference in scores on a tolerance scale (7%) can be
explained by between-country variance. The χ² of the likelihood-ratio test comparing the
standard model to a two-level one has shown the latter model to be significantly better
than standard OLS regression, justifying the need for multilevel analysis. Table 1 shows
that the full individual-level model explains about 42% of between country variance in
tolerance scores, with economic threat variables (income, employment status,
employment history and perceived economic performance of the country) adding most
explanatory value to the model. The results of from the full individual-level model are
displayed in table 2.
TABLE 1.
Variance components for model with individual level explanatory
variables
Null model
Individual level model
Demographic
variables
Education level
Variables
Economic
threat variables
Individual level
variance
3.722
3.675
3.435
3.276
Between country
variance
0.290
0.283
0.252
0.168
0
0.012
0.077
0.12
0
0.025
0.13
0.42
Explained individual
level
variance
Explained country
level
variance
In the initial model, it appears that the younger the individuals, the more tolerant they
were likely to be. The tolerance levels decrease with age until the respondents reach the
mean age of 47.3 years, when their tolerance seems to increase as they get older. This
effect seems to be inversed once educational variables are accounted for and once
reaching a mean age of 47.3 the respondents tend to become less tolerant with the
passage of time. This is likely due to the fact that to a certain point, the older the
respondents, the more likely they are to have reached full secondary and tertiary
education. However, once they reach the 38-45 age category at which the educational
level is highest, there is a steep decrease in the amount of respondents with an
educational level higher than primary (see figure 2 in appendix 1). Similarly, the initial
effect of being male on tolerance level (increase in 0.1 points on the tolerance scale)
seems to disappear with the introduction of education variables. This is most likely
because men, on average, tend to be more educated than females. This finding
contradicts that of Semyanov et al. (2008) who find that women, on average, tend to be
more prejudiced than men. Secondary education tends to increase overall tolerance by
0.4 point and tertiary education by a little over 1 full point even when other variables are
controlled for in the full individual level. This suggests, as predicted, that education
increases tolerance levels among individuals. This finding is not surprising, given that
educational attainments are likely to improve one’s economic security by increasing
employment opportunities. Furthermore, it is also likely that education has a positive
correlation with tolerance through promulgation of specific values, such as development
of pro-democratic attitudes and appreciation for diversity (Hyman and Wright, 1979).
Educated respondents are also more likely to appreciate the potential economic benefits
of foreign labour and feel less threatened by their presence.
It is clear from table 2 that economic satisfaction is a strong and significant predictor of
tolerance, as expected in hypothesis 2. An increase of one point in economic satisfaction
level results in almost 2 point increase on the tolerance scale. These effects are visible
even when accounting for factors such as income, unemployment history or being
currently unemployed and seeking for work. This confirms the expectation that low levels
of satisfaction are likely a reflection of perceived economic threat from immigrants to the
country’s general population, not only individual’s self-interest.
Finally, neither being unemployed, having a history of unemployment, or the interaction
between the two seems to have any significant impact on tolerance score in the model.
Table 2. Full individual model
Estimates of fixed parameters
β
+
Demographic
variables
+ Education
variables
+ Economic
variables
(indiv.)
Constant
8.429***
4.496***
4.876***
Age, in years
-0.067***
0.004
-0.145
Square rooted age, centred
0.768***
-0.154***
-0.034
Male gender
0.092***
0.073***
0.020
Secondary education
0.420***
0.387***
Tertiary education
1.241***
1.093***
Age*tertiary education
0.002*
0.002**
Male*tertiary education
0.024
-0.016
Satisfaction with economy
0.175***
Ever unemployed for a period of at least 3 months
0.0119
Unemployed, actively seeking work
-0.040
Ever unemployed for at least 3 months*unemployed,
actively seeking work
-0.105
Medium income
0.098***
High income
0.265***
Figure 4 provides a more detailed view of how the subjective view of economic
performance affects the mean tolerance score. There is a very clear positive relationship
between economic satisfaction and tolerance. Poland and Sweden are clear outliers where
positive attitudes towards foreign migrants seem to correlate with economic satisfaction
to a much lesser degree. It is likely that the coefficient in the first model (table 2) would
be much higher if the outliers were to be removed.
Figure 4. The relationship between perceived satisfaction with state’s
6
7
economy and mean scores on the tolerance scale
4
5
Sweden
3
Poland
4
4.5
5
5.5
Mean score on the tolerance scale
6
6.5
Figure 5 below demonstrates the strength of the relationship between subjective
economic satisfaction and tolerance scores by ESS wave. Apart from the first wave (2002)
where the slope is visibly less steep than in other waves, the relationship seems to be
rather stable. Scores on economic satisfaction scale were lower in 2008, 2010 and 2012
wave, which corresponds with the deteriorating economic conditions after the 2008
financial crisis.
Figure 5. The relationship between perceived satisfaction with state’s
2
3
4
5
6
7
economy and scores on the tolerance scale, by wave
0
2
4
6
8
10
Score on the tolerance scale
2002
2006
2010
2004
2008
2012
Source: ESS 2002-2012
Table 3 shows the result from a model with the addition of two contextual variables
(mean GDP per capita and mean unemployment rate) and the satisfaction with economy
variable into the random-coefficient model. The likelihood ratio tests suggest that
addition of each country-level variable at level two significantly improves the model.
The results from the full two-level model are presented in table 4. Age, education and
income remain highly significant predictors of tolerance. Mean unemployment rate does
not seem to have a significant effect on tolerance levels. Surprisingly, the increase in
mean GDP per capita tends to decrease, rather than increase the scores on the scale. A
possible explanation for the effect is the fact that despite the 2008 economic crisis, GDP
per capita has been steadily increasing most countries. Another explanation could be the
fact that the change in mean GDP per capita scores has not been prominent enough to
have the predicted effect on discriminatory attitudes. This contradicts hypothesis 3 which
states that the higher the GDP per capita, the higher the scores on the tolerance scores.
Similarly, hypothesis 4 stating that higher unemployment rates would lead to decrease in
tolerance scores has also been disproved. Nevertheless, economic satisfaction remains a
highly significant predictor of anti-immigrant attitudes. The visual representation of these
results can be seen in figures 2 and 3 in the appendix, which show the effects of mean
GDP per capita change and economic satisfaction change on tolerance for specific
countries.
These results are surprising, and might be due to one of the following factors. Firstly, it is
possible that subjective perceptions of economic satisfaction are unrelated to real
changes in economic performance and are simply a more powerful predictor of antiimmigrant prejudice. This could suggest that the rhetoric of economic crises, whether
substantiated by actual changes in performance or not, affects respondents to a much
greater degree than real changes in economic growth or unemployment level. These latter
two factors might simply be unperceivable to the respondents, who might not always
follow the current economic trends of their countries. In future research, it would perhaps
be useful to control for the level of political interest expressed by survey participants.
Secondly, it is equally likely that GDP per capita and unemployment level are not good
predictors of real economic performance. For example, it is possible that relative change
in unemployment would be a much more helpful measure of the current economic
conditions than the percentage of people who are currently out of work. A 10% level of
unemployment might have a different significance for Poland than it does for Sweden.
Some countries might have a naturally high level of informal economy, where officially
unemployed citizens still engage in economic activity without officially participating in it.
Similarly, in some countries it might be more natural for women to stay at home, making
the unemployment rate higher without reflecting potential economic hardship. A more
focused cross-country comparison in the future could offer some insights into which
countries should be examined together, and which indicators would best predict economic
performance.
Table 3. The final model
Full model
Estimates of fixed parameters
β
Std. error
t
Constant
7.43***
0.657
11.31
-0.008**
0.003
-2.84
0.007
0.035
0.21
Age
Square rooted age, centred
Male gender
0.016
0.011
1.45
Secondary education
-0.678***
0.034
-20.06
Tertiary education
1.062***
0.035
30.21
Age*tertiary education
0.002**
0.001
68.53
Male*tertiary education
-0.007
0.021
4.45
Satisfaction with economy
0.181***
0.011
15.81
Ever unemployed for a period of at least 3 months
0.014
0.011
1.22
Unemployed, actively seeking work
-0.048
0.062
-0.77
Ever unemployed for at least 3 months*unemployed,
actively seeking work
-0.105
0.067
-1.57
Medium income
0.097***
0.012
8.45
High income
0.251***
0.013
20.02
Wave 1
-0.786***
0.109
-7.19
Wave 2
-0.714***
0.069
-10.20
Wave 3
-0.460***
0.037
-12.36
Wave 5
-0.152***
0.022
-6.94
Wave 6
-0.012
0.029
-0.41
Square root of GDP per capita
-0.010***
0.002
-3.96
Natural logarithm of mean
unemployment rate
0.063
0.148
0.43
Finally, it is worth mentioning the effects of the wave in which the respondents have been
interviewed and the possible effects of the economic crisis on the perception of threat
from foreign workers. The reference category in the group was year 2008 (wave 4).
Tolerance towards immigrants in 2008 is statistically greater than tolerance in 2002 and
2006 waves. The tolerance in the subsequent wave (2010) is also significantly lower than
that in 2008. This confirms the initial findings from figures 2 and 3 earlier in this section.
CONCLUSION
Although research on RGCT has been growing in recent years, with many studies finding a
positive correlation between unfavourable economic conditions and the presence of antiimmigration attitudes, the results of this paper are mixed. Firstly, the hypothesis stating
that respondents would be more likely to score lower on the tolerance scale between 2008
and 2012 relative to the 2002-2006 period has not been confirmed. Clearly, the economic
crisis itself has not influenced people’s views of foreign workers in the manner
hypothesized by RGCT. On the other hand, it suggests that social contact theory might be
a worthy competitor in terms of explaining the presence or absence of prejudice in
European society. The more socialization between immigrants and the in-group as the outgroup population increases, the lower the level of threats expressed by the majority.
Secondly, the perceived economic performance was a much better predictor of antiimmigrant attitudes than contextual variables. While unemployment seems to have had no
statistically significant impact on the tolerance scale, growth in GDP per capita has
actually decreased tolerance scores across all 15 investigated countries apart from Poland.
These findings are important because it suggests either that contextual variables are not
relevant when accounting for anti-foreign attitudes or that unemployment levels and GDP
per capita are not reliable measures of economic prosperity. Future studies could
investigate sudden changes in unemployment or GDP per capita levels on anti-foreign
prejudice as there are more likely to reflect economic turbulence within the state.
Despite contextual variables having no or little effect on prejudice expression, one aspect
of RGCT has been confirmed: people who rate the economic conditions in the country
unfavourably were most likely to express negative views of immigration, regardless of
their educational level or income. This suggests that prejudice towards foreign workers
might be independent of any immediate threats to one’s economic security, as predicted
by Bobo (1986). Prejudice expression might indeed be partially dependent on the relative
threat to the entire in-group as opposed to the individual herself. It is also possible that
an individual’s perception of economic disadvantage, even when unsubstantiated by GDP
figures, has a significant impact on anti-foreign sentiments.
Finally, individual-level variables seem to have had a pronounced effect on prejudice
expression. Particularly, those in more advantaged economic situation (with a high level
of education, and high income) seem to have the most favourable views of foreign
workers’ impact on the economy, culture and living conditions within the state. The
overall conclusion of the paper is that contextual predictors of prejudice should be
approached with caution and a much more discussion on operationalization of these
variables should be included in future research. Furthermore, more attention should be
paid to subjective interpretation of environmental factors, as this paper suggests they are
a very strong predictor of anti-foreign attitudes. While the RGCT assumptions have not
been substantiated fully by this paper, it is likely that this is due to relatively low
construct validity rather than incorrect theoretical specifications.
Appendix 1. Table 1. Definition for the individual-level and country-level variables included in
the analysis
Individual level variables
Definition
Age
Square root of age, centred
Male gender
Education
In years
In years
Man = 1 (%)
What is the highest level of education you have successfully
completed?
Secondary = 1 (%)
Tertiary = 1 (%)
Secondary education
Tertiary education
Age*tertiary education
Male*tertiary education
Interaction between age and having tertiary education
Interaction between being male and having tertiary
education
Satisfaction with economy
On the whole how satisfied are you with the present state of
the
economy in [country]?
0-10 scale: 0 = extremely dissatisfied, 10 = extremely
satisfied
Unemployed
Unemployment history
Using this card, which of these descriptions applies to what
you have been doing for the last 7 days? Select all that
apply.
Unemployed = 1 (%)
Income
Have you ever been unemployed and seeking work
for a period of more than three months?
Yes = 1 (%)
Using this card, please tell me which letter describes your
household's total income, after tax and compulsory
deductions, from all sources? If you don't know the exact
figure, please give an estimate. Use the part of the card
that you know best: weekly, monthly or annual income
High
Medium
Wave
Tolerance items
Recode of the income variable, country specific.
High = 1 (%)
Medium = 1 (%)
European Social Survey round
Would you say it is generally bad or good for [country]’s
economy that people come to live here from other
countries?
0-10 scale: 0=bad for economy, 10=good for economy
And, using this card, would you say that [country]’s cultural
life is generally undermined or enriched by people coming to
live here from other countries?
0-10 scale: 0=cultural life undermined, 10=cultural life
enriched
Is [country] made a worse or a better place to live by
people coming to live here from other countries?
0-10 scale: 0=worse place to live, 10=better place to live
Country-level variables
Definition
Mean GDP (square root of)
Mean Gross Domestic Product per capita, in $1000,
calculated for every three years between 2000 and 2012
Mean unemployment (natural logarithm of)
Mean unemployment rate (%) for all ages, calculated for
every three years between 2000 and 2012
Appendix figure 2. A visual representation of the effects of
economic satisfaction on tolerance scores, by country.
Appendix figure 3. A visual representation of the effects of the
increase in mean GDP per capita on tolerance scores, by country.
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