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. 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