Realistic Group Conflict Theory and Economic Threats: A ...€¦ · Allport (1954/79: 29-33) theorized that familiarity, fundamental to human survival, becomes a value shared with

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 non-

material 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 anti-

foreign sentiments in Europe. Although deteriorating economic conditions do not affect

the entire population of a country, they are nonetheless likely to result in increased anti-

immigrant 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 anti-

foreign 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 anti-

immigrant 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 sample1. 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 anti-

immigrant 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 well-

being 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.

Figure 3. Changes in tolerance scale score distribution by ESS wave

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.

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44

.55

5.5

66

.5

Me

an

sco

re o

n th

e to

lera

nce

sca

le

2002 2004 2006 2008 2010 2012

Source: EVS 2002-2012

ESS wave

Sweden

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

Explained individual level

variance

0

0.012

0.077

0.12

Explained country level

variance 0 0.025 0.13 0.42

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

economy and mean scores on the tolerance scale

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.

Poland

Sweden

34

56

7

Mea

n s

co

re o

n the

eco

nom

ic s

atisfa

ction s

cale

4 4.5 5 5.5 6 6.5

Mean score on the tolerance scale

Figure 5. The relationship between perceived satisfaction with state’s

economy and scores on the tolerance scale, by wave

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

23

45

67

Sco

re o

n e

co

nom

ic s

atisfa

ctio

n s

ca

le

0 2 4 6 8 10

Score on the tolerance scale

2002 2004

2006 2008

2010 2012Source: ESS 2002-2012

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 anti-

immigrant 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

Age

-0.008** 0.003 -2.84

Square rooted age, centred 0.007 0.035 0.21

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 anti-

immigration 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 out-

group population increases, the lower the level of threats expressed by the majority.

Secondly, the perceived economic performance was a much better predictor of anti-

immigrant 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 Secondary education Tertiary education Age*tertiary education Male*tertiary education Satisfaction with economy Unemployed Unemployment history Income High Medium Wave Tolerance items

In years In years Man = 1 (%) What is the highest level of education you have successfully completed? Secondary = 1 (%) Tertiary = 1 (%) Interaction between age and having tertiary education Interaction between being male and having tertiary education 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 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 (%) 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 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 unemployment (natural logarithm of)

Mean Gross Domestic Product per capita, in $1000, calculated for every three years between 2000 and 2012 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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