Attitudes to immigrants and integration of ethnically diverse societies

Attitudes to immigrants and
integration of ethnically
diverse societies
Tiiu Paas, Vivika Halapuu
University of Tartu, Estonia
International Workshop
at the GALLAGHER ACADEMY OF PERFORMING ARTS
University of Waikato
Wednesday 11 April – Friday 13 April 2012
The main focus of the study
• The paper focuses on examining the attitudes of European
people to immigration emphasizing possible diversity of peoples’
attitude depending on
• personal characteristics;
• some peculiarities of the countries where they live.
• The overwhelming aim of the study is to get empirical evidence
based grounds for policy proposals that can support integration
of ethnically diverse societies and create favorable conditions for
economic growth.
Why? Motivation
• Many countries experiencing an increase in anti-immigrant attitudes.
Thus, elaboration and implementation of new policy measures that can
support integration of ethnically diverse societies is necessary.
• Determinants of future economic growth (Florida 2002, 2004): 3T
approach
– Technology: concentration and development of high technology and
innovation;
– Talent: human capital; concentration of educated, innovative and
creative people.
– Tolerance: openness to diverse ethnicities, races, cultures, walk of
life, etc.
• Attitudes to immigrants can be considered as a proxy of tolerance.
Theories explaining determinants of attitudes
towards immigration are interdisciplinary
Two group of (interlinked) theories: individual and collective.
•
•
Individual
– Individual economic theories (related to human capital, personal income,
employment);
– Cultural marginality theory (e.g. cultural conflicts),
– Political affiliation theories (level of political involvement),
– Integration theory (interpersonal trust);
– Neighborhood safety theory; contact theory
Collective (regional and national)
– Collective economic theory (related to GDP pc, labour market situation);
– Contact theory (the share of immigrants);
– Historical background, path-dependence
Data and methods
Data
•
European Social Survey 4th round database, which includes 30 European
countries.
•
Our study covers data of 28 202 respondents from 25 European countries
(Bulgaria, Cyprus, Slovak Republic Israel and Turkey excluded):
– respondents’ individual characteristics (sex, age, education, labour
market status, work experience, religion, etc.)
– respondents’ attitudes towards countries’ institutions, socio-economic
situation, and immigrants (answers to the questions).
Methods
– Method of principal component factor analysis to elaborate aggregated
indicators of peoples attitudes.
– Regression analysis to explore determinants of peoples’ attitudes
towards immigration.
Aggregated indicators of respondents’ attitudes
Questions
1.Immigration bad or good for country's economy
2.Country's cultural life undermined or enriched by
immigrants
3.Immigrants make country worse or better place to live
5. How likely unemployed and looking for work next 12
months
6 . How likely not enough money for household necessities
next 12 months
7. How likely not receive health care needed if become ill
next 12 months
Aggregated indicators of attitudes to…
Socioeconomic
Institutions
Immigrants
security
(political trust)
0.753
0.778
0.798
0.619
0.851
0.822
8. Trust in country's parliament
9. Trust in the legal system
10. Trust in the police
11. Trust in politicians
12. Trust in political parties
KMO
0.875
0.837
0.752
0.899
0.977
0.731
0.592
Source: the method of principal component factor analysis is implemented using the ESS data
0.817
Regression model
• Dependent variable (Y) – individual’s attitudes to immigration
(factor scores of the composite indicator).
• Independent variables (X):
– Personal chracteristics of individuals (age, sex, living place,
education, religion, country of birth, working abroad, etc)
– Factor scores of composite indicators (political trust,
socio-economic risk)
– Country dummies
Sample: European Social Survey, 28 202 respondents from 25 countries
.
Robust OLS estimators of the model describing
European peoples’ attitudes towards immigration
Coefficient
Robust
standarderror
Significance
Constant
Income (ref. group – low)
-0.288
0.042
0.000
Middle
0,013
0,013
0,324
High
0,089 ***
0,015
0,000
Labour market status (ref. group - out of labour force)
Unemployed
-0,010
0,026
0,440
Employed
0,004
0,013
0,745
Socio-economic security
0,078 ***
0,007
0,000
Level of education (ref. group – low)
Middle
0,140 ***
0,014
0,000
High
0,366 ***
0,015
0,000
Not born in a country
0,347 ***
0,019
0,000
Ever belonged to a group discriminated against
0,062 ***
0,020
0,002
Experience of working abroad
0,089 ***
0,023
0,000
Political trust
0,266 ***
0,006
0,000
No children
0,017
0,011
0,130
Feeling of safety when walking in the neighbourhood
when it’s dark
0,034 ***
0,007
0,000
Not a crime victim
0,002
0,013
0,909
Age
-0,003 ***
0,000
0,000
Gender (ref. group - female)
-0,009
0,011
0,397
Not belonging to a particular religion
0,057 ***
0,012
0,000
Domicile (ref. group - countryside)
Small town
0,061 ***
0,013
0,000
Big city
0,102
***
0,013
0,000
Number of cases (N)
28 202
Prob>F
0,000
R2
0,244
*** p < 0,01. Dependent variable: factor scores of the aggregated indicator of individuals’ attitudes
towards immigrants and immigration. Country dummies are included.
Source: authors’ estimations based on the ESS data.
Empirical results
•
The results are consistent with several theories at both individual and collective
level.
– Higher level of education promotes higher level of tolerance to immigrants .
– People with higher income have better attitude to immigrants.
– People who trust countries’ institutions (e.g. political trust) and people who
have better expectations to their own socio-economic security are more
tolerant to immigrants.
– People who are not born in the country where they live, people who have
worked abroad are as a rule more tolerant to immigrants (in support of
contact theory).
– People living in urban areas are more tolerant to immigrants. (Heterogeneity
promotes tolerance, contact theory ).
– Personal characteristics of the respondents that are not changeable on the
country level (age, sex, religion, ethnicity) are statistically significantly related
to the respondents’ attitudes towards immigrants; e.g. young people, no
religious people have better attitudes to immigrants.
– Surprisingly, labour market status does not have significant impact on
attitudes to immigrants.
Respondents’ attitudes toward immigrants vary between
the countries
The Baltic States
(2010)
Country
Population
(mil)
The share
of ethnic
minorities
(%)
The share of
the new
immigrants
GDP
GDP pc
pc (PPP) comparing
EU, %
Estonia
1.3
32.3
0.3
18 400
70
Latvia
2.2
40.7
0.2 (0.4)
13 200
54
Lithuania
3.3
16.0
0.3 (0.5)
15 300
58
Robust OLS estimators of regression models describing peoples’ attitudes
towards immigration in the Baltic States
Estonia
Latvia
Lithuania
0.328*
-0,074
-0,089
0.115
-0.111
0.165*
0.568***
-0,131 *
0.091
-0,052
-0,068
0,048
0.092
-0.068
0.055
-0,150
-0, 099
0,086**
0,108
0,230***
0,405***
0,256**
0,127
0,224***
0,021
-0,095
-0.096
0,358***
0,191**
0,029
0,188***
0,119**
0,090
0,110
0,373***
-0.351***
0,055
0,179***
0, 113*
-0.002
0,040
-0,010***
0,035
-0,045
-0,018
-0, 120
- 0, 080***
0, 014
-0,108
Constant
Income (ref. group – low): Middle
High
Labour market status (ref. group - out of labour force)
Unemployed
Employed
Socio-economic security
Level of education (ref. group – low)
Middle
High
Not born in a country
Ever belonged to a group discriminated against
Experience of working abroad
Political trust
No children
Feeling of safety when walking in the neighbourhood
when it’s dark
Not a crime victim
Age
Gender (ref. group - female)
Not belonging to a particular religion
Domicile (ref. group - countryside)
Small town
0,021
-0.075
-0.013***
0,083
-0.340
-0.010
0,228***
-0,082
Big city
0.022
0,036
-0,039
Number of cases (N)
1018
1120
990
Prob>F
0,000
0.000
0.000
R2
0,137
0.100
0.106
*** p < 0,01; ** p < 0,05; * p < 0,01.
Dependent variable: factor scores of the aggregated indicator of respondents’ attitudes towards
immigrants.
Source: authors’ estimations based on the ESS data, 2008.
Note: Chow test is used for examining statictical significance of structural change.
What is different in the case of the Baltic States?
• The patterns of attitudes to immigrants in The Baltic States as small countries with postsocialist historical background (path dependence) are statistically different from the whole
sample (Chow test).
• Attitudes to immigrants are better if
• Attitudes to political institutions are higher
• Young
• Born outside this country.
• Latvian and Estonian people are less tolerant to immigrants (comparing to reference
country Belgium); Lithuanian people are more tolerant (the share of minorities is ca 16%,
in other two countries around 1/3 and even more (Latvia).
• Higher education relates to improvement of tolerance towards immigrants only in the case
of Estonia.
• Higher income and/or higher socio-economic security improves attitudes to immigrants in
the case of Latvia and Lithuania.
• Experience of working abroad do not improve (yet? ) attitudes towards immigration.
Conclusion
•
European peoples’ attitudes towards immigrants are in general consistent with several
theoretical considerations.
•
The variation of respondents’ attitude towards immigration can be explained by
– personal characteristics of the respondents (age, sex, education, personal
experience of working abroad, place of living);
– peoples’ attitudes towards countries’ institutions (political trust) and their socioeconomic security (estimations of future personal well-being);
– country specific conditions (e.g. path- dependence).
•
Policy implications
– to improve stability of socio-economic situation and conditions allowing to
increase people’s trust to their countries institutions;
– to create supportive conditions for (temporal) labour mobility between countries;
– to encourage and support people to improve their educational level;
– to take into account the composition of countries’ population (e.g. age, sex,
religion, ethnicity)
- case by case studies are necessary for elaborating integration policies.
Thank you!
Comments and suggestions
are welcome
[email protected]