Anti-Immigrant Attitudes in Europe: Outgroup-size and Perceived Ethnic Threat

Silke Schneider Department of Sociology/Nuffield College

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Contents   Research question   Theory   Hypotheses   Previous research   Method   Results   Conclusions   The big BUT…

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Research Question   Does the actual presence of immigrants

influence anti-immigrant attitudes in a country?

  How?   Why?

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Ethnic Competition Theory I: Context   Attitudes and behaviour between groups

primarily serve the maintenance of the groups’ status position.

  The more conflict and competition between two social groups, the stronger are negative attitudes against the outgroup expressed by ingroup members.

  Conflict and competition over what? •  Economic resources, social status • Cultural values, traditions, national identity

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Ethnic Competition Theory II: Still context Assumption: The larger the outgroup (with

constant resources), the more intergroup conflict and competition. Thus:

  the larger an economically threatening outgroup (holding economic resources constant)

and/or (?)   the larger a culturally threatening outgroup,   the more perceived ethnic threat on the

side of the ingroup.

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Ethnic Competition Theory II: The Individual   Also the need to preserve one’s individual

status may lead to the rejection of an outgroup, particularly if its members are perceived as threatening the individuals’ social status.

  There is more competition between immigrants and members of the majority population in social niches that don’t require much education, i.e. low status jobs. Thus:

  The lower an individuals socio-economic status,

  the more perceived ethnic threat felt by these individuals.

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Intergroup contact theory and Familiarisation   Contact between members of different social groups

improves the group members’ attitudes vis-à-vis each other (given certain conditions are met). Contact hypothesis

  Why? Contact is the most basic condition for familiarity, maybe even friendship.

  Assumptions: •  The larger the outgroup, the more contact

opportunities between in- and outgroup. •  Familiarisation over and above the effects of direct

contact (e.g. indirect contact through the media)   Thus: The larger the outgroup,   the weaker is ethnic threat perceived by the ingroup

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Linking ethnic competition and intergroup contact theory   Outgroup size measures both competition and

contact opportunities, which counteract. Thus, both theories have to be taken into account (e.g. contact has to be controlled for on the individual level).

  It can be assumed that competition and familiarity increase simultaneously.

  Modified hypothesis on the effect of outgroup-size: at higher levels of outgroup-size, outgroup-size does not increase ethnic threat perceptions any more (Familiarisation).

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Cross-level interaction hypotheses I: Competition*outgroup size interaction   A larger outgroup is economically more

threatening to people who have a low socio-economic status.

  If there are no immigrants, even low status individuals cannot perceive ethnic threat on realistic grounds (theoretically).

  Thus, the larger the outgroup, the stronger the expression of prejudice against the outgroup among ingroup members with a low socio-economic status.

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Cross-level interaction hypotheses: Contact*outgroup size interaction   A larger outgroup is culturally more threatening

to people who do not have any contact with members of that group than for those who do.

  People who have contact with immigrants have more such contacts when the outgroup is larger.

  Thus, the larger the outgroup, the stronger the expression of prejudice against the outgroup among ingroup members without outgroup contact.

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Overview over the hypotheses

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Previous studies: Issues   e.g. Quillian (1995), Scheepers et al. (2002),

McLaren (2003), Semyonov et al. (2006)   Economic and cultural conflict are not

differentiated empirically – some authors prefer an economic interpretation of outgroup size effects, others prefer cultural accounts.

  Immigrants as the outgroup are equated with the percentage of non-(EU‑)citizens in a specific country.

  Non-EU-citizenship is taken as a proxy for immigrants with low qualifications.

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Methods and Data   European Social Survey (ESS) 2002/2003   Ethnic threat perception index (mean score) built from 6 items:

D25 Using this card, would you say that people who come to live here generally take jobs away from workers in [country], or generally help to create new jobs?

D26 Most people who come to live here work and pay taxes. They also use health and welfare services. On balance, do you think people who come here take out more than they put in or put in more than they take out?

D27 Would you say it is generally bad or good for [country]’s economy that people come to live here from other countries?

D28 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?

D29 Is [country] made a worse or a better place to live by people coming to live here from other countries?

D30 Are [country]’s crime problems made worse or better by people coming to live here from other countries?

Source: Norwegian Social Science Data Services (2004)

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Individual level predictors   Social status:

•  income (≤ 50% of the average equivalence income; 50 to 80%; 80 to 120%; ≥ 120%; no response).

•  occupational status (self-employed; unemployed; employed: manual workers, routine-non-manual, complex non-manual; otherwise not gainfully employed: students, retirees and housekeepers)

•  education in years   Subjective degree of difficulty to change the job or

the employer   Type of living area (large city and its suburbs or in a

small town/the country)   Intergroup contact:

•  immigrant friends •  immigrant colleagues •  people of a minority race or ethnic group in current living area

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Country level predictors   Source: The OECD’s database on immigrants

and expatriates (OECD, 2005) •  Economically threatening outgroup: share of low-

educated immigrants (defined as those with lower secondary education or less, i.e. ISCED 0, 1 and 2)

•  Culturally threatening outgroup: share of immigrants from non-western countries

•  Familiarisation: outgroup-size squared

  Source: World Bank, 2004 •  Economic resources (control): average real GDP per

capita (rGDP/c) from 1997 to 2001

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Statistical method: Multilevel modelling   Regression analysis of clustered sample data   dependent variable is located on the individual level

and the independent variables are found on at least two levels of analysis

  variance explained by attributes of the context and variance explained by attributes of the individual are separable

  Contextual and individual effects as well as interaction effects between contextual and individual variables are modelled simultaneously

  standard errors are estimated correctly

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Results: Descriptive cross-national differences

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Multilevel Models: Overview (fit) D0 = –

2*loglikelihood ∆ =

D0-D1 d.f. p

Model 1: empty fixed intercept 130852.5 Model 2: empty random intercept 126932.9 3919.7 1 0.000 Model 3: Model 2 + respondent level predictors 122830.7 4102.2 22 0.000 Model 4: Model 3 + country level predictors

Model 4a: GDP and % low educated immigrants + squ. 122825.9 4.8 3 0.187 Model 4b: GDP and % non-western immigrants + squ. 122822.2 8.5 3 0.037

Model 5: Model 4 with cross-level interactions with % immig.

Model 5a: interactions between % immigrants and poor, manual, unemployed, urban, education

122815.7 10.2 5 0.070

Model 5b: interactions between % immigrants and immigrant friends, immigrant colleagues, immigrants in living area, urban

122738.7 83.5 4 0.000

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Multilevel Models: Overview (fit) D0 = –

2*loglikelihood ∆ =

D0-D1 d.f. p

Model 1: empty fixed intercept 130852.5 Model 2: empty random intercept 126932.9 3919.7 1 0.000 Model 3: Model 2 + respondent level predictors 122830.7 4102.2 22 0.000 Model 4: Model 3 + country level predictors

Model 4a: GDP and % low educated immigrants + squ. 122825.9 4.8 3 0.187 Model 4b: GDP and % non-western immigrants + squ. 122822.2 8.5 3 0.037

Model 5: Model 4 with cross-level interactions with % immig.

Model 5a: interactions between % immigrants and poor, manual, unemployed, urban, education

122815.7 10.2 5 0.070

Model 5b: interactions between % immigrants and immigrant friends, immigrant colleagues, immigrants in living area, urban

122738.7 83.5 4 0.000

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Multilevel Models: Overview (fit) D0 = –

2*loglikelihood ∆ =

D0-D1 d.f. p

Model 1: empty fixed intercept 130852.5 Model 2: empty random intercept 126932.9 3919.7 1 0.000 Model 3: Model 2 + respondent level predictors 122830.7 4102.2 22 0.000 Model 4: Model 3 + country level predictors

Model 4a: GDP and % low educated immigrants + squ. 122825.9 4.8 3 0.187 Model 4b: GDP and % non-western immigrants + squ. 122822.2 8.5 3 0.037

Model 5: Model 4 with cross-level interactions with % immig.

Model 5a: interactions between % immigrants and poor, manual, unemployed, urban, education

122815.7 10.2 5 0.070

Model 5b: interactions between % immigrants and immigrant friends, immigrant colleagues, immigrants in living area, urban

122738.7 83.5 4 0.000

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Multilevel Models: Overview (fit) D0 = –

2*loglikelihood ∆ =

D0-D1 d.f. p

Model 1: empty fixed intercept 130852.5 Model 2: empty random intercept 126932.9 3919.7 1 0.000 Model 3: Model 2 + respondent level predictors 122830.7 4102.2 22 0.000 Model 4: Model 3 + country level predictors

Model 4a: GDP and % low educated immigrants + squ. 122825.9 4.8 3 0.187 Model 4b: GDP and % non-western immigrants + squ. 122822.2 8.5 3 0.037

Model 5: Model 4 with cross-level interactions with % immig.

Model 5a: interactions between % immigrants and poor, manual, unemployed, urban, education

122815.7 10.2 5 0.070

Model 5b: interactions between % immigrants and immigrant friends, immigrant colleagues, immigrants in living area, urban

122738.7 83.5 4 0.000

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Multilevel Models: Individual level Model 5a Model 5b

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Multilevel Models: Individual level Model 5a Model 5b

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Multilevel Models: Individual level

What does this mean?

Model 5a Model 5b

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Multilevel Models: Individual level Model 5a Model 5b

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Multilevel Models: Individual level Model 5a Model 5b

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Multilevel Models: Individual level Model 5a Model 5b

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Multilevel Models: Individual level

Self-selection… Self-selection…

Model 5a Model 5b

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Multilevel Models: Country level Model 5a Model 5b

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Multilevel Models: Country level Model 5a Model 5b

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The non-linear effect of outgroup size

Predicted score on the index of perceived ethnic threat

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Multilevel Models: Country level

Lots left unexplained…

Quite ok!

Model 5a Model 5b

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Conclusions: context   Not the economic status (low education) of immigrants, but their

non-western origin adds to the average level of perceived ethnic threat in European countries. The higher the percentage of non-western immigrants, the higher the country’s average level of perceived ethnic threat.

  Thus, the proportion of non-EU citizens (as used in other studies) proxies culturally unfamiliar immigrants rather than low educated immigrants.

  the relationship between the percentage of culturally distant immigrants and average perceived ethnic threat is not linear: the effect levels off

  This result limits the validity of ethnic competition theory: A large outgroup does not only increase competition, but it also increases contact opportunities and familiarity with immigrants

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Conclusions: Individuals   Effects of low socio-economic status are independent of the

size of an economically threatening outgroup (low-educated immigrants), so they cannot be explained by realistic economic competition between low-status majority population and immigrants. Thus, economic threats at the individual level seem rather distorted than real

  Contact with immigrants limits ethnic threat perceptions; and the effect of outgroup-size is weaker for individuals with intergroup contact than for individuals without

  Residual variance left on both levels of analysis - incomplete explanations

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BUT… “Information on the proportion of foreign-born population with education at ISCED levels 0-2 presented in the paper can absolutely not be trusted. It is not clear to me how this figures where calculated, at any rate they do not concur with anything I have seen thus far. Please re-check this information, consult other sources, e.g. Eurostat EULFS data, and you will get absolutely different and actually more realistic figures. The levels of low-secondary education for immigrants reported in Table A1 (and not Table 4 as stated on page 18) are extremely low, which does not reflect the reality, and unless these are corrected and the models re-estimated the paper cannot be published in its present form.”

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Hooooooray, another revision!*

* that will keep me away from my PhD thesis for a while…

Thank you for you comments.