Welfare threat and exclusionism of immigrants. Perception of immigrants in different European welfare states. (Radka Klvaňová)

 

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1. Immigration, welfare state and xenophobia

 

Immigration into Western Europe after the Second World War followed various tracks[1], and as a result of these immigration processes, an environment of cultural and ethnic heterogeneity emerged in Europe, which brought a new challenge for the European, so far relatively ethnically homogeneous, societies organized in the forms of nation states.

            Not only was the cultural environment affected by immigration, but also the institutional structure of the modern nation states was confronted.  “International migration in its various forms challenges organizational and conceptual boundaries, borders, important forms of social organization, such as the welfare state, as well as ways of thinking about ‘us’ and ‘them’ (Geddes, 2003a: 2). The civil, political and social rights originally conceptualized as the exclusive entitlements of the native population forming the contract between the state and citizens were partially extended also to some of the newcomers (Phalet, Swyngedow, 2002). The state organized solidarity, founded originally on the notion of ethnically based citizenship that indicated the community of legitimate receivers of welfare state provision, has been challenged.

            The welfare state is one of the most powerful institutions that immigrants are confronted with in the European countries in a sense that it determines their position in the society in different ways and divides them into various categories (Ireland, 2004: 5). As a tool of both inclusion and exclusion the welfare state system also became a method of regulation of migration by means of providing welfare support to some migrants and denying it to others (Geddes, 2003b: 153).

The immigrants living and arriving in European countries often face negative attitudes of the natives. This creates a barrier for their further integration into the society and increases tensions between the ethnic groups. However, the attitudes towards immigrants vary across countries, and yet not many studies tried to explain those differences, since they rather focused on finding the similarities explaining xenophobia across Europe. This study aims at finding whether living in a particular welfare state affects the perception of immigrants as a source of threat to the welfare of the native population, and thus whether the differences in the attitudes towards immigrants in various European countries can be explained by the structural differences.

 

 

1.1 Welfare state types

 

There are different types of welfare states based on different ideas of social solidarity. In my paper, I use Esping-Andersen’s typology of welfare states (1990, 1999). He distinguishes among three welfare state regimes. Firstly, the liberal welfare state emphasizes the market dominance in welfare provision that is distributed according to one’s efforts on the labour market and stresses the individual responsibility for one’s well-being. The level of decommodification or independence from the market is the lowest among all the welfare state regimes, and the basis for the social rights entitlement is a demonstrated need of the deserving poor. State organized horizontal as well as vertical solidarity is on a very low level. Secondly, the conservative-corporatist welfare state type is based on the principle of subsidiarity and thus the role of the state in the welfare provision is limited to the situations where the lowest networks of solidarity, especially the family, fail. The degree of decommodification is limited and the horizontal solidarity is favoured over the vertical solidarity. The society is strongly segmented according to the status derived from the position on the labour market, which is the main basis for the benefits entitlement. Thirdly, the social democratic welfare state regime emphasizes the principle of universal solidarity and the entitlement for social rights is based on citizenship. The degree of decommodification is the highest among the three welfare regimes and the state takes the responsibility for social welfare of its citizens. An extensive vertical redistribution attempts to minimize the market as well as family dependency.

One of the topics discussed in the context of the welfare state and immigration is the effect of the generosity of the welfare state on the extent of immigration and the type of immigrants. An extensive research on the effect of immigration on the welfare state exists (e.g. Borjas, 1999; Razin, Sadka, 2004, Lundborg, Segerstrom, 2002, Brücker et al., 2001), but there is no room for discussion of these effects in this paper. Most authors conclude that immigration can put a burden on the welfare state, but the effect of the immigration on the welfare state depends on the characteristics of the immigrants. An evidence exists that countries with the most generous welfare system can act as welfare magnets and attract immigrants that are more likely to depend on the welfare system (so-called welfare migration) (Brücker et al., 2001: 57, 82).

 

 

1.2 Theories of ethnic relations

 

This section provides an overview of the main theories of ethnic relations referring to xenophobia, racism, prejudice, and ethnic exclusionism that, even if labeled differently in the literature, provide explanations of the negative attitudes of the natives towards the immigrants.

      Wimmer (2000) provides a helpful summary of the theories of racism and xenophobia and he distinguishes among four main explanations of xenophobia and racism[2]: the rational choice theory, functionalism, sociobiology and discourse theory.

            First, according to the rational choice theories, the natives perceive the immigrants as illegitimate rivals in the competition over scarce resources and xenophobic discourse helps to legitimate their position in this competition. The realistic conflict theory comes from the conflictualist sociological paradigm. Coser (1956) argues that competition over scarce resources between social groups is inherent in every social system. Blumer (in Quillian, 1995) develops a concept of a collective threat, which results in prejudice of the dominant group against the subordinate group, because the dominant group views its group position in relation to the subordinate group, that is perceived as threatening their position and their ownership of certain resources belonging exclusively to the dominant group members. Those theories claim that increased competition between ethnic groups for scarce resources or the availability of those resources for redistribution puts pressure on the inter-ethnic relations (Ederveen et. al, 2004: 74). The theory of economic self-interest claims that the members of the same economic structure share common interests and each class citizen supports policy that maximizes his own utility. This theory also presents the immigrants as a threat to the natives’ economic well-being (Gusfield in Fetzer, 2000). On the individual level, negative attitudes towards ethnic minorities and immigrants emerge at individuals who are in competition and conflict with them (Quillian, 1995: 587). The theory of labour market versus use of services explains the hostility towards immigrants among native population by the fear that immigrants will take away their jobs because they will accept lower wages and they will also reduce their wages in the low skilled jobs. Moreover, the natives fear that they will have to pay more taxes because the increasing number of immigrants will use the publicly funded services (Muller, Espenshade in Fetzer, 2000).

            Second and third type of theories explaining xenophobia in Wimmer´s classification, functionalism and sociobiology provide an explanation of xenophobia and racism based on perception of cultural differences. The inability of the foreigners to overcome them and integrate into the receiving society feeds xenophobia according to the functionalist discourse, and the fear of cultural incompatibility is the main source of xenophobia in the sociobiological discourse.

            The fourth type in Wimmer´s classification is the discourse theory that does not focus on the cultural differences of the immigrants, but rather on the construction of xenophobia in a discourse of power groups, who define the social situations of economic or political crises and label the immigrants as those responsible for the problems in society. Moreover, labeling of the immigrants based on their ethnic differences through the administrative and discursive practices reinforces the perceptions of them as distinct from the native population.

            Wimmer proposes his own thesis of xenophobia and racism called struggle over collective goods, where he combines both collective and individual mechanisms of formation of xenophobic attitudes. He proposes that racism and xenophobia are closely related to the basic characteristics of the nation state representing interests of ethnically defined community, and as such it serves as basis for the legitimization of xenophobic discourses and the reinforcement of national identity. Immigrants do not fit into the image of shared national history, when the institutions like the welfare state were created by joint labour effort, and thus the xenophobic discourses of exclusion tend to show the immigrants as people who came to unjustly claim the right for the collective wealth. Moreover, in times of economic recession or welfare state instability immigrant groups with high unemployment rates or asylum seekers are perceived as those who impede the state in its welfare provision to those who are members of the “true,” legitimately entitled community.  However, because the xenophobic discourses are mainly heard by the members of the community who are most threatened by crises in the society, the negative attitudes towards immigrants are not equally distributed along the social strata. Thus people with low level of education and bad prospects of future career, who are also most likely to depend on the mechanisms of organized social solidarity, seem to be most appealed by the xenophobic discourses of exclusion (Wimmer, 2000).

            Coenders (2001) presents a valuable concept of ethnic exclusionism when explaining the negative perception of immigrants and ethnic minorities by the native majority group, and also combines both the individual and collective level perspective. Ethnic exclusionism is an outcome of the competition between ethnic groups at both individual and contextual level that increases the perceived ethnic threat, which consequently reinforces the mechanisms of social identification and contra-identification. According to the theory of ethnic competition, which combines the realistic conflict theories and theories of social identification, the stronger the actual competition, the stronger the perceived ethnic threat (Coenders, 2001: 42-43).

 

 

1.3 Welfare state and attitudes towards immigrants: hypotheses and expectations

 

It stems from the overview of the theoretical perspectives above that the institutional structure of modern nation states, and the welfare state based on the ethnically demarcated solidarity in particular, is an important factor in shaping the attitudes towards immigrants. The immigrants can be perceived as a threat to the well-being of the native population, and especially in time of social and economic crises, they are perceived as those who contributed to their emergence. My approach to the analysis of the negative attitudes towards immigrants combines the theoretical thoughts of the rational choice theories, theories on the welfare state and immigration, and the conceptualization of Wimmer (2000) and Coenders (2001) with the idea of Svallfors (1997 in Arts, Gelissen, 2001) who claims that the attitude structure and value commitments are to a large extent based on contextual factors, particularly on the type of the welfare state.

The study aims at answering two research questions:

 

1. How does the perceived welfare threat determine the exclusionism of immigrants by the native population in different European welfare states? 

2. How do the individual socioeconomic characteristics vary in their effect on the exclusionism of immigrants and how do they interact with the perceived welfare threat in different European welfare states?

 

            Following the classification of the welfare state regimes of Esping-Andersen (1990, 1999) and the different notions of solidarity behind those distinct regimes, I expect that the perception of immigrants as a source of threat to the welfare of the native population differs across the welfare states regimes. Following Ederveen et al. (2004) and the idea of welfare migration (Brücker et al., 2001), I expect that in countries with a broad concept of solidarity and large redistribution across the society, immigrants will be perceived as a larger threat to the welfare of the natives, which will form a strong determinant of the exclusionism of immigrants. In the welfare states where the market and individual self-reliance is emphasized and the redistribution is minimal, the perceived threat to the welfare of the natives from the side of immigrants can be expected to be a weaker predictor of the exclusionism of immigrants. I call this hypothesis a redistribution hypothesis.

            However, the logic of explanation of the effect of the type of state organized solidarity on the attitudes towards immigrants can also be reversed. Coenders, Lubbers and Scheepers (2003a) also hypothesize that living in a particular welfare state can have an effect on ethnic exclusionism. They refer to a degree of decommodification, hence the protection against social risks that differs between the welfare states, and put forward that the competition over scarce resources can be modified by the state, depending on the degree to which the state takes responsibility for the welfare provision. On the one hand, in welfare states with high level of decommodification, the competition over scarce resources within the society is reduced both with the members of the community and the immigrants, and hence the perception of immigrants as a threat to the welfare of the native population as well as the exclusionism of immigrants decreases. On the other hand, in the states with weak decommodification, the competition over scarce resources is sharpened, and thus the immigrants are perceived more as a threat to the welfare of the native population. I call this hypothesis a decommodification hypothesis.

            The contextual level characteristics that influence the formation of attitudes towards immigrants can also interact with the individual characteristics. The degree of decommodification varies across welfare states, and thus also the extent to which the competition over scarce resources is reduced. Following the rational choice theory logic, individuals who hold similar position as immigrants in the system of social stratification are more likely to compete with the immigrants than the others. The degree of decommodification in the particular welfare state can thus have an important impact on the perceived threat to the welfare of the native population, and consequently on the degree of exclusionism of immigrants. Therefore, I expect that the social position in the stratification system of the individuals from the native population will be more important in predicting the exclusionism of immigrants due to their higher perceived welfare threat in countries with low decommodification than in countries, where the independence from the market is guaranteed by the state. Certain categories of people such as the elderly, low skilled people and people with low income tend to be more dependent on the mechanisms of organized solidarity than other people. Therefore, I focus on testing the effect of those characteristics and their interaction with the perceived welfare threat on the exclusionism of immigrants.

 

1.4 Overview of existing research

 

The research about the welfare state regime influence on the perception of immigrants is scarce. Coenders, Lubbers and Scheepers (2003b) found that in countries with high GDP per capita, where more resources are available for redistribution, and the competition for scarce resources can be reduced, the ethnic exclusionism is lower. O´Rourke and Sinnott (2004) found that the effect of high-skills on more favourable attitudes towards immigrants is greater in countries with less inequality.

            Moreover, some researchers also attempt to indicate to what extent the concerns about the welfare system and the economy are manifested in the negative attitudes towards immigrant groups (Dustmann, Preston, 2000; Ederveen et al., 2004). Dustmann and Preston (2000) found evidence that welfare worries are associated with negative opinion toward further immigration to the United Kingdom, but they concluded that the racial prejudice was the most important factor. They also found that welfare and labour market concerns are more strongly associated with the negative attitudes towards immigration of non-manual workers and more educated people than of manual workers and less educated people.

            Regarding the socioeconomic characteristics as determinants of attitudes towards immigration, Gang, Rivera-Batiz and Yun (2002) in their analysis of the Eurobarometer surveys of 1988 and 1987 found that Europeans who directly compete with immigrants on the labour market have more negative attitudes towards non-European Union citizens. However, recent research of Hainmueller and Hiscox (2005), who used European Social Survey data from 2003, showed that high skilled and highly educated people are more in favor of immigration compared to people with low skills and education, regardless of the rival potential of the immigrants, and thus they deny that the labour market competition theory explain the negative attitudes towards immigration. Coenders, Lubbers and Scheppers (2003b) in their analysis of determinants of immigrants´ exclusionism found that people with low educational levels, in the lowest income quartile, depending on social security, older people and those attending regularly religious services had more negative exclusionist stances.

 

 

2. Research design and measurement instruments

 

The research is designed as a cross-national comparison of the perception of immigrants in different welfare state regimes. The focus of the research is not to find general similarities of the immigrants´ perception across the welfare states, but it rather attempts to find the differences that are specific within the particular welfare regime context with respect to the perception of immigrants. Thus an attention is paid more to the social structure dimension and its impact on the formation of distinctive perceptions of immigrants, rather than to individual processes of attitudes´ construction. However, in practice those two dimensions interact with each other in the formative process of perception of immigrants (Verkuyten, ter Wal, 2000).

Esping-Andersen in his theory indicated three models of welfare regimes and has classified several Western countries according to this typology. In Europe, the only liberal welfare regime can be found in the United Kingdom, the conservative-corporatist welfare regime is represented in Germany, Austria, France and Italy and the Scandinavian countries are prototypes of the social-democratic welfare state (Esping-Andersen, 1990: 27). To measure the concept of the welfare regimes countries representing the distinct types are selected. In order to increase the power of the causal inference two countries from each welfare regime were selected with expectations that the same tendency will reveal in both of them due to their specific institutional configuration. Liberal welfare regime forms an exception because in Europe only one country representing this type can be found in reality. Thus United Kingdom as the liberal welfare state, Germany and Austria representing the conservative-corporatist type of the welfare state and Denmark and Sweden as archetypes of the social democratic welfare state were selected for the comparison[3].

 

 

2.1 Data collection

 

In the research the data from European Social Survey (Round 1, 2002/2003) are used for the analysis. The survey gathered data based on nation-wide samples of 22 countries including United Kingdom, Denmark, Sweden, Germany and Austria and comprises a module devoted to attitudes, perceptions, policy preferences and knowledge on immigration and asylum issues. The data was gathered by interviewers from all the countries in face-to-face interviews from September 2002 till mid 2003[4].

 

 

2.2 Sampling strategy and weighting

 

The European Social Survey applied strict and rigorous sampling strategy in order to create equivalent and representative country samples with respect to the population size and characteristics. The stratified random sampling method was used with requirements for full coverage of the target group, high response rate, no substitution and the same minimum effective sample size in participating countries[5]. However, not all the samples reached enough representativeness, and thus following the recommendation of the authors of the ESS, I use weights that are designed to correct for the differences in probabilities of selection in the sample. Those weights, however, do not correct for variation between different groups neither for non-response in the sample[6].

When studying the attitudes of the native population towards immigrants it is important to distinguish between the respondents from the majority non-immigrant population and the respondents who came to live in the country, or are the descendants of the immigrants. Thus I limited the analysis only to the respondents from the majority population of non-immigrant origin. I chose those who were born in the respective country and at least one of their parents as well, and in the paper I call them “native population”[7]. The rest of the sample was dropped (i.e. 12.6% of the total sample in Austria and Sweden, 12.4% in the United Kingdom, 10.9% in Germany and 6.2% in Denmark). Moreover, cases with missing values on more than 50% of the variables used in the analysis were also excluded from the sample. After those transformations there are 1967 cases in Austria, 2599 cases in Germany, 1392 cases in Denmark, 1738 cases in Sweden and 1795 cases in the United Kingdom.

 

 

2.3 Non-response and missing values treatment

 

Large non-response and missing values on the variables of interest can bias the results, but there was no weight created to correct for non-response in the sample. The response rate target for the ESS is set to 70% but not all the countries managed to reach this target. From the countries of interest the highest response rate was reached in Sweden (69%) and Denmark (68.4%). The response rate in the rest of the selected countries was lower: 60.6% in Austria, 55% in the United Kingdom and 53.7% in Germany. Billiet and Meuleman (2005) simulated the correction of non-response for several ESS samples with respect to gender, age and education, but they found out that even if some non-response bias can be eliminated by this weighting the amount of the eliminated bias is minimal compared to the remaining bias.

            Non-response on the items included in the analysis can be another source of bias, in case that respondents differ systematically from non-respondents, and it also diminishes the size of the sample. In order to avoid a large reduction in the sample size due to missing values when creating the scales used in the analysis I took into consideration respondents that gave answer at least on the 50% of the items forming the scale following the rule used in scientific journals (Coenders, Lubbers, Scheepers, 2003b: 56). Missing values of the respondents chosen on the basis of this rule were replaced by their mean score on the rest of the items.

 

 

2.4 Measurement instruments, variables and the method of analysis

 

The ESS questionnaire was not designed for the purpose of the present research but it contains many important items related to the topic that is discussed in this paper. Thus it is possible to use those items as indicators of the above mentioned concepts[8]. The exclusionism of immigrants is the dependent variable, and it is measured by three questions on the extent of immigration the country should allow with respect to the background of the immigrant. I followed the image of immigrants the respondents expressed in the ESS answering the question on the ethnic and economic background of most immigrants coming to their countries. The greater part of the native population perceived that the majority of immigrants coming to their country had different ethnic or race origin and came from poorer countries rather than richer countries (see table 2A in the Annex)[9].

            The key independent variable is the perceived welfare threat measuring the extent to which natives perceive immigrants and immigration as a threat for the welfare of their countries. It is measured by five items on the perception of the effects of immigration on country’s economy, the labour market and the use of welfare services.

            Moreover, individual background variables such as gender, age[10], education[11], income[12], International Socio-Economic Index of Occupational Status (ISEI) (Ganzeboom, Treiman, 1996a)[13], and church attendance[14] are controlled for in the analysis. Those individual characteristics vary across countries and they showed significant impact on the attitudes towards immigrants in previous research (Coenders, Lubbers, Scheepers, 2003b; Quillian, 1995; Hainmueller, Hiscox, 2005; O´Rourke, Sinnott, 2004).

            When comparing the perception of immigrants across countries, it can be also important to control for contextual variables on the macro level. Those characteristics vary across countries[15] and previous research showed different results with respect to their impact on the perception of immigrants. In his study of twelve European countries, Quillian (1995) found that the relative size of the immigrants´ population and the economic situation in a country has an impact on the prejudice expressed by the majority native population. Coenders (2001) compared 22 countries with respect to ethnic exclusionism and found a link between the economic situation of the country, increase in inflow of asylum seekers and the exclusionism of immigrants. However, the relationship between the proportion of ethnically different population and exclusionism of immigrants was not confirmed. Finally, in their comparative analysis across European countries, Coenders, Lubbers and Scheepers (2003b) did not found any impact of unemployment, level of GDP, proportion of non-western foreign born population, number of asylum applications and net migration on the resistance towards immigrants.

            In the analysis, I wanted to control for the impact of the unemployment level, proportion of non-western immigrants in the population, number of asylum applications and net migration on the exclusionism of immigrants, not to obtain the effect of those characteristics on the exclusionism of immigrants, but to single out the effect of the other variables included in the analysis. However, it turned out that most of the contextual effects are strongly correlated among each other and, where the characteristics of the country are the highest from all the countries, they also correlate strongly with the dummy variable for the respective country[16]. Thus there is a problem of high multicollinearity among the independent variables and its negative consequences for the results[17]. Since the purpose of the analysis is to assess the differences among the countries, it is not desirable that their coefficient estimates might be biased. Therefore, in order to avoid this bias, I do not control for those contextual effects in the analysis, but those characteristics are described and discussed in the Annex, Table 5A.

Multiple ordinary least square regression is used as a method of analysis of the effect of perceived threat to the welfare on the exclusionism of immigrants. First, separate analyses are run for every country. Second, all the countries are included in the same regression equation in order to assess the differences between the countries more in details. 

 

 

2.5 Comparability

 

Although the European Social Survey is a research project applying strict methodological rules, the quality of the data is not the same in every country, and the data is not always directly comparable across countries (see Billiet, 2005). It is behind the scope of present paper to test for the comparability of the data across countries, and thus I rely on several studies assessing the quality and comparability of the ESS data, and also, the use of the data in previous research.

            Billiet (2005) shows some traps in the ESS cross-nation research, mainly concerning the problems with translations, also in connection with the effects of the context. Thus for my research, I avoid using items from the ESS survey that were found problematic in the previous research. Moreover, Billiet and Welkenhuysen-Gybels (2004) assessed cross-national construct equivalence of the six items, on the extent of immigration respondents thought their country should allow, with respect to the ethnic and economic background of the immigrants. The authors concluded, that even if the scale constructed of those six items was not scalar invariant, it was metric invariant, which is the minimum level of equivalence required for measuring the same latent variable with the same set of indicators across all the countries (Billiet, Welkenhuysen-Gybels, 2004: 16). However, following Coenders, Lubbers and Scheppers (2003b), who acknowledged that in some countries the respondents (in the case of present research it was Denmark and Germany) distinguished between the immigrants from poor and rich countries and the immigrants with different race or ethnic origin, and following the image the respondents had about the majority of immigrants in all the countries, I included only three items on the extent of immigration from the six included in the questionnaire[18].

 

 

3. Results

 

In this chapter, the results of the regression analysis are presented, and the hypotheses are tested. First, I describe how the key variables, exclusionism of immigrants and the perceived welfare threat, differ across countries. Second, to answer the first research question, I discuss how the perceived welfare threat determines the exclusionism of immigrants by the native population in different European welfare state. Third, I present the conclusions for the second research question, how the individual socioeconomic characteristics vary in their effect on the exclusionism of immigrants, and how they interact with the perceived threat to welfare in different European welfare states.

 

 

3.1 Perceived threat to welfare and the exclusionism of immigrants in different welfare regimes

 

First, description of the dependent variable exclusionism of immigrants and the key independent variable perceived welfare threat in the selected countries is shown in Table 1. The descriptive statistics for other independent variables included in the analysis are presented in the Table 1A in the Annex.

 

Table 1: Means and standard deviations for exclusionism of immigrants and perceived threat to welfare in selected countries

 

Exclusionism of immigrants

(1-low; 4-high)

Perceived threat to welfare

(1-low; 5-high)

Country

Mean

Std.Dev.

Mean

Std.Dev.

Austria (N=1967)

2.64

0.68

3.10

0.70

Germany (N=2599)

2.34

0.68

3.27

0.67

Denmark (N=1392)

2.37

0.66

2.93

0.63

Sweden (N=1738)

1.95

0.65

2.79

0.61

United Kingdom (N=1795)

2.58

0.74

3.30

0.68

Source: ESS 2002/2003, author’s computations

 

            The strongest exclusionism of immigrants is found in Austria with the mean value of 2.64 on the four points scale. United Kingdom follows with the mean value of 2.58, Germany and Denmark are somewhere in the middle, and Sweden has the lowest score on the scale of exclusionism of immigrants from all the countries (1.95). The analysis of variance shows that the differences among the countries are statistically significant (F = 270.9; df = 4, 9224; p < 0.001). Games-Howell post-hoc test of the pairwise differences between the countries indicates that the difference between Austria and the United Kingdom, and Germany and Denmark in the exclusionism of immigrants is not statistically significant (p > 0.05).

            People in the United Kingdom and Germany perceive immigrants as the strongest threat to the welfare of their country from all the countries with the mean value of 3.3 on the five point scale, followed by the Austrians and the Danish. The lowest threat to the welfare from the side of the immigrants is perceived by respondents in Sweden, which also corresponds to their favourable attitudes concerning the acceptance of immigrants. Comparison of the means of the separate countries on the scale perceived welfare threat shows that the differences among the countries are statistically significant (F = 193.3; df = 4, 9275; p < 0.001). However, a closer investigation of the means differences in the Games-Howell post hoc test shows that the differences in the mean perceived welfare threat are not significant when comparing Germany and the United Kingdom.

In order to answer the first research question, how the perceived threat to welfare determines the exclusionism of immigrants by the native population in different European welfare states, I conduct, first, separate regression analyses for every country of interest and, second, I include all the countries in one regression equation in order to be able to assess the differences between the countries.

The first estimated model can be considered as a series of k regression equations, such that:

Eik = ak + Xikßk + eik,                                                                           (1)

where Eik is the level of exclusionism of immigrants for individual i in country k. Xik is a matrix of 9 independent variables in country k, ßk is the corresponding estimated coefficient and ak is the intercept for country k, and eik is an error term.

            The results of the multiple OLS regression analyses conducted separately for every country are shown in Table 3A in the Annex. The effects of the perceived welfare threat are statistically significant at the 1% level and the magnitude of its effect is the highest from all the independent variables included in the model (comparing standardized betas). The effect is the highest in the United Kingdom, which is also the country with the strongest exclusionism of immigrants. On the exclusionism of immigrants scale of 1 to 4, one unit change on the perceived welfare threat scale ranging from 1 to 5 is expected to increase the exclusionism of immigrants by 0.560, controlling for the individual background characteristics. However, the effect of perceived welfare threat on the exclusionism of immigrants is the second highest in Sweden (ß=0.493), which is the country with the lowest perceived welfare threat and the lowest exclusionism of immigrants. It is followed by Germany (ß=0.441); Denmark (ß=0.402) and Austria (ß=0.371) show the lowest effect of the perceived threat to welfare on the exclusionism of immigrants from all the countries.

            All the independent variables included in the model explain 24% of the variance of the exclusionism of immigrants in Austria, 26% in Denmark, 29% in Germany, 31% in Sweden, and 37% in the United Kingdom. Clearly the amount of explained variance follows the pattern of the magnitudes of the effects of perceived welfare threat across the countries.

            The results concerning the effect of the perceived welfare threat on the exclusionism of immigrants do not follow the pattern of welfare regimes which would mean that Denmark and Sweden would show similar results, and Austria and Germany too. Thus the expectations that the countries belonging to the same welfare regime show the same tendency in the effect of the perceived threat to welfare on the exclusionism of the immigrants are not met.

However, the regression coefficients from the separate regression equations do not show, how large the differences of the effects of the perceived welfare threat on the exclusionism of immigrants are between the countries. For this purpose the countries are included in the same regression equation, which allows assessing the significance of the differences between the countries:

Ei = a + Xißi + ATß1 + DEß2 + DKß3 + SEß4 + AT*PWTß5 + DE*PWTß6 + DK*PWTß7 + SE*PWTß8 + ei,                           (2)

where Ei is the level of exclusionism of immigrants, a is the intercept, Xi is the matrix of 9 independent variables included in the model, ßi are the corresponding regression coefficients. ß1 to ß4 are the estimated coefficients for the country dummies, ß5 to ß8 are the estimated coefficients for the interaction terms of the variable perceived welfare threat and the dummy variables for each country, and ei is an error term. United Kingdom is the reference country in this model.

            Parameter estimates for the above mentioned model are shown in the Table 2 below. Model 1 shows the regression estimates for the independent variables from the pooled data analysis, when all the samples of the five countries are included in the regression equation, but without adding the dummy variables for the countries. In model 2, the dummy variables for the four countries are added in the analysis, and the differences in the intercepts in the different countries are shown. Finally, model 3 includes also the interaction terms of the variable perceived welfare threat and the country dummies, and thus the differences in the effects of the perceived welfare threat on the exclusionism of immigrants in different countries are indicated.

            In model 2, the predicted values on the exclusionism of immigrants in separate countries, when controlling for the perceived welfare threat and the socio-demographic characteristics, can be assessed. In the hypothetical situation when all the independent variables have zero value, and assuming there are no method effects in the separate countries Austria has the highest predicted value on the exclusionism of immigrants (1.692[19]), followed by the United Kingdom (1.526) and Denmark (1.386) that do not differ significantly from each other. Germany (1.311) and Sweden (1.110) have the lowest predicted exclusionism of immigrants.

 

Table 2: Parameter estimates from ordinary least square regression analysis of exclusionism of immigrants
(all countries included in the model)

Independent variables

Model 1

Model 2

Model 3

Perceived welfare threat

0.494**

(0.010)

0.457**

(0.010)

0.564**

(0.021)

Education

-0.024**

(0.003)

-0.027**

(0.002)

-0.028**

(0.002)

Age (ref: 26 - 55)

 

 

 

- 15 – 25

-0.167**

(0.022)

-0.169**

(0.021)

-0.172**

(0.021)

- 56 +

0.058**

(0.015)

0.081**

(0.015)

0.081**

(0.012)

Male (ref. = female)

-0.008

(0.015)

-0.011

(0.013)

-0.013

(0.013)

Income

-0.00001

(0.000004)

-0.00001**

(0.000004)

-0.00001**

(0.000004)

ISEI

-0.003**

(0.001)

-0.002**

(0.001)

-0.002**

(0.001)

Country (ref.=UK)

 

 

 

Austria

 

0.166**

(0.021)

0.792**

(0.096)

Germany

 

-0.215**

(0.019)

0.196*

(0.091)

Denmark

 

-0.014

(0.022)

0.469**

(0.103)

Sweden

 

-0.415**

(0.021)

-0.158

(0.096)

Country x perceived welfare threat (PWT) (ref.=UK)

 

 

 

Austria x PWT

 

 

-0.195**

(0.029)

Germany x PWT

 

 

-0.124**

(0.027)

Denmark x PWT

 

 

-0.151**

(0.033)

Sweden x PWT

 

 

-0.007*

(0.031)

Church attendance (ref.= never)

 

 

 

- once a month

0.058**

(0.019)

-0.018

(0.019)

-0.014

(0.019)

- rarely

-0.0004

(0.015)

0.013

(0.014)

0.015

(0.019)

Intercept

1.261**

(0.050)

1.526**

(0.052)

1.169**

(0.079)

Adjusted R²

0.298

0.370

0.373

Note: N = 8,337; **parameter estimate is significant at the 1% level (p-value < 0.01); *parameter estimate is significant at the 5% level (p-value < 0.05). Numbers in parentheses are standard errors.

Source: ESS 2002/2003, author’s computations

            In model 3, when controlling for the individual background characteristics the perceived welfare threat is the strongest predictor of exclusionist stances in the United Kingdom (0.564), and this effect differs significantly from the other countries. The strength of the effects varies across the other countries, but after testing the differences between other pairs of countries[20], I conclude that when following the order according to the magnitude of the effect – the lowest in Austria (0.369[21]), then Denmark (0.413), Germany (0.439) and Sweden (0.492) - the countries next to each other do not differ significantly from each other. Austria does not differ significantly from Denmark, Denmark does not differ significantly from Germany, and Germany and Sweden do not differ significantly in the effect of perceived welfare threat on the exclusionism of immigrants.

From the perspective of the welfare regime theory, in the United Kingdom, representing the liberal welfare regime, the perceived welfare threat influences most intensely the exclusionism of immigrants compared to the other countries representing different welfare regimes. This result supports the decommodification hypothesis, stating that the level of decommodification influences the competition over scarce resources, and not the redistribution hypothesis, stating that the level of redistribution influence the effect of perceived welfare threat on the exclusionism of immigrants. However, according to the decommodification hypothesis, in the countries with the highest decommodification, the effect of perceived welfare threat on the exclusionism of immigrants should have been the lowest, which is not the case shown in the results of the analysis. While in one of the representative countries of the social democratic regime (Denmark) the effect of the perceived welfare threat is among the weakest from all the countries, in the other one (Sweden) the effect of the perceived welfare threat is the second strongest, not the weakest as was hypothesized. Moreover, the countries representing the same welfare regime differ significantly from each other in the effect of the perceived welfare threat on the exclusionism of immigrants.

            The results show that the effects of the perceived threat to the welfare from the immigrants´ side differ across countries. However, no clear relationship between the type of welfare regime and the effect of the perceived welfare threat on the exclusionism of immigrants exists.

 

 

3.2 Individual socio-economic characteristics, perceived welfare threat and the exclusionism of immigrants

 

In this part, I answer the research question, how the individual socioeconomic characteristics vary in their effect on the exclusionism of immigrants, and how they interact with the perceived welfare threat in different European welfare states. Separate regression analyses are conducted for this purpose, and stepwise regression method is used, to determine whether the interaction effects of the socio-economic characteristics – income, occupational status and age – with the perceived welfare threat exist. The results of the regression analysis are presented in Table 3A and Table 4A in Annex[22].

            Controlling for other background characteristics and perceived welfare threat, the International Socio-Economic Index of Occupational Status has a slight negative effect on the exclusionism of immigrants, which is statistically significant on the 0.01 level in Germany and Sweden. People with higher occupational status have, on average, lower tendency to exclude immigrants in Germany and Sweden. However, no interaction effect of the occupational status and the perceived welfare threat on the exclusionism of immigrants emerged.

            Controlling for the rest of the variables in the regression analysis, income has no statistically significant impact on the exclusionism of immigrants in any of the countries, nor is there a different effect of perceived welfare threat on the exclusionism of immigrants depending on the level of income.

            Age is a significant predictor of the exclusionism of immigrants in all the countries when controlled for the other background variables and the interaction effect of age and perceived welfare threat. People aged 15 to 25 have significantly less exclusionist stances than people aged 26 to 55 in all the countries, except for Sweden. People older than 56 show stronger tendency towards exclusionism of immigrants as compared to the people aged 26 to 55 in all the countries, except for Denmark. No interaction effect of age and perceived welfare threat exists, except for Sweden[23] (weaker effect of perceived welfare threat on the exclusionism of immigrants among those older than 56 compared to the middle age group).

            Concerning the other control variables included in the analysis, men have on average more exclusionist stances than women in Germany and Denmark, while in the United Kingdom it is the reverse. Education has a significant negative effect on the exclusionism of immigrants in all the countries. Church attendance has a significant impact only in Austria and the United Kingdom. In Austria, people who attend religious services have, on average, more exclusionist attitudes towards immigrants than people who never go to church. The effect is reversed in the United Kingdom, where people who go to church at least once a month have, on average, significantly less negative exclusionist stances than people who never attend religious services.

The hypothesis that the individual socio-economic characteristics are more important predictors of the exclusionism of immigrants in countries with less decommodification (strong effect in the United Kingdom, moderate effect in Germany and Austria) than in countries with high level of decommodification has not revealed true. No clear welfare regime type based pattern concerning the effect of the individual characteristics on the exclusionism of immigrants and their interaction with the perceived welfare threat emerged.

 

 

4. Discussion and conclusion

 

This paper aimed at indicating whether living in a particular welfare state affects the perception of immigrants as a source of threat to the welfare of the native population and how it determines the exclusionism of immigrants. The main finding of the study is that the perception of immigrants as a source of threat to the welfare among the native population differs across countries, but no clear relationship between the type of welfare regime and the effect of the perceived welfare threat on the exclusionism of immigrants exists. Even if the impact of the individual background characteristics on the exclusionism of immigrants differs across the countries, and it does not always show the same tendency and significance, there is no welfare regime based pattern of the effect of the individual socioeconomic characteristic on the exclusionism of immigrants.

            The study suggests that the welfare regime theory cannot explain the differences in xenophobia in various European countries. Thus a question arises: which other factors can explain the differences in exclusionism of immigrants across countries? Why is the perceived welfare threat such a strong determinant of the exclusionism of immigrants in the United Kingdom compared to Austria, given that both countries have almost the same level of xenophobia?

            The country’s macro-level characteristics such as the proportion of foreign born population, number of asylum seekers or unemployment level do not seem to provide a satisfactory explanation since they showed ambiguous results in previous research. Moreover, Wallace (1999: 11) remarks that it is not so much about the actual extent of immigration as about its perception, and the way how the issue of immigration is expressed in public discourse.

            Some authors tried to explain the differences in attitudes towards immigrants across countries with type of immigration policy. Bauer, Lofstrom and Zimmermann found an evidence that country’s immigration policy affects which immigrants come to the country, their economic performance, and thus also their perception by the native population. Their findings suggest that in countries that select the immigrants according to the needs of the labour market (Canada, New Zealand) the natives perceived them as generally good for the economy, than in countries that receive mainly refugees (the Netherlands, Sweden) (Bauer, Lofstrom and Zimmermann in Brücker et al., 2001: 53).

            The study of immigration policy determinants of the natives´ attitudes towards immigrants or the comparison of public discourses could be the possible directions to go further to explore the factors determining the varying degrees of xenophobia across European countries. Comparative analysis of the attitudes towards immigrants in different countries can reveal the causes of xenophobia that can be consequently to some extent eliminated by various policies in order to ameliorate the inter-ethnic relations and facilitate the integration of the growing number of immigrants in European countries.
 

 

Annex

 

A1. Annex 1: Tables

 

Table 1A: Means and standard deviations for the independent variables

Variables

Austria

(N=1967)

Germany

(N=2599)

Denmark

(N=1392)

Sweden

(N=1738)

UK

(N=1795)

 

Mean (Std.Dev.)

Mean (Std.Dev.)

Mean (Std.Dev.)

Mean (Std.Dev.)

Mean (Std.Dev.)

Perceived welfare threat

3.10 (0.70)

3.27 (0.67)

2.93 (0.63)

2.79 (0.61)

3.30 (0.68)

Education

12.27 (2.90)

12.93 (3.33)

13.24 (3.60)

11.89 (3.40)

12.55 (3.16)

ISEI

43.32 (13.97)

44.21 (15.20)

41.92 (16.81)

42.90 (16.84)

42.36 (16.84)

Male

0.48 (0.50)

0.48 (0.50)

0.52 (0.50)

0.51 (0.50)

0.49 (0.50)

Income

2,327 (1,311)

2,659 (1,646)

3,316 (1,870)

2,505 (1,371)

3,207 (2,312)

Age 15-25

0.15 (0.35)

0.13 (0.34)

0.12 (0.33)

0.14 (0.35)

0.13 (0.34)

Age 26 - 55

0.59 (0.49)

0.52 (0.50)

0.54 (0.50)

0.50 (0.50)

0.50 (0.50)

Age 56 +

0.27 (0.44)

0.35 (0.48)

0.33 (0.47)

0.36 (0.48)

0.36 (0.48)

Church attendance

 

 

 

 

 

- once a month

0.35 (0.48)

0.19 (0.39)

0.09 (0.28)

0.11 (0.31)

0.16 (0.36)

- rarely

0.38 (0.49)

0.44 (0.50)

0.52 (0.50)

0.51 (0.50)

0.31 (0.46)

- never

0.26 (0.44)

0.37 (0.48)

0.39 (0.49)

0.38 (0.48)

0.54 (0.50)

Note: Means for the categorical variables show the proportions of the categories in the sample.

Source: ESS 2002/2003, author’s computations

 

Table 2A: Majority’s image of the ethnic and economic background of immigrants in their country

Race/ethnic background of most immigrants

Austria

N=1967

Germany

N=2599

Denmark

N=1392

Sweden

N=1738

UK

N=1795

Same as majority

5%

10%

5%

15%

4%

Different than majority

73%

68%

70%

46%

69%

Half and half

22%

22%

25%

40%

27%

Economic background of most immigrants from Europe

 

 

 

 

 

Richer countries

2%

1%

3%

8%

3%

Poorer countries

80%

91%

66%

60%

76%

Half and half

18%

8%

31%

32%

21%

Economic background of most immigrants from outside Europe

 

 

 

 

 

Richer countries

2%

1%

1%

4%

2%

Poorer countries

84%

93%

88%

81%

80%

Half and half

14%

5%

11%

15%

18%

Source: ESS 2002/2003, author’s computations

 

Table 3A: Parameter estimates from separate ordinary least square regression analyses of exclusionism of immigrants

Independent variables

Austria

(N=1559)

Germany

(N=2207)

Denmark

(N=1264)

Sweden

(N=1600)

UK

(N=1708)

Perceived welfare threat

0.371** (0.023)

B=0.383

0.441**

(0.019)

B=0.440

0.402**

(0.026)

B=0.381

0.493**

(0.023)

B=0.460

0.560**

(0.022)

B=0.519

Education

-0.028**

(0.006)

B=-0.119

-0.024**

(0.005)

B=-0.117

-0.041**

(0.006)

B=-0.227

-0.024**

(0.005)

B=-0.122

-0.024**

(0.005)

B=-0.103

Age

(ref: 26 - 55)

 

 

 

 

 

- 15 - 25

-0.227**

(0.048)

B=-0.108

-0.197**

(0.048)

B=-0.076

-0.192**

(0.054)

B=-0.091

-0.074

(0.043)

B=-0.038

-0.158**

(0.046)

B=-0.070

- 56 +

0.115**

(0.036)

B=0.075

0.060*

(0.027)

B=0.043

-0.022

(0.037)

B=-0.016

0.125**

(0.034)

B=-0.092

0.118**

(0.033)

B=0.078

Male (ref. = female)

-0.006

(0.030)

B=-0.005

0.055*

(0.040)

B=0.021

0.076*

(0.032)

B=0.058

-0.007

(0.006)

B=-0.019

-0.067*

(0.029)

B=-0.046

Income

-0.000002

(0.00001)

B=-0.004

-0.00001

(0.000008)

B=-0.027

-0.00001

(0.00001)

B=-0.032

-0.00001

(0.00001)

B=-0.022

-0.00001

(0.00001)

B=-0.039

ISEI

0.001

(0.001)

B=-0.018

-0.003**

(0.001)

B=-0.069

-0.001

(-0.001)

B=-0.030

-0.003**

(0.001)

B=-0.068

-0.001

(0.001)

B=-0.031

Church attendance (ref.= never)

 

 

 

 

 

- once a month

0.161**

(0.039)

B=0.116

-0.047

(0.035)

B=-0.027

-0.010

(0.062)

B=-0.004

-0.079

(0.048)

B=-0.037

-0.134**

(0.042)

B=-0.067

- rarely

0.146**

(0.038)

B=0.106

-0.034

(0.027)

B=-0.025

0.057

(0.034)

B=0.043

0.013

(0.029)

B=0.010

-0.027

(0.032)

B=-0.017

Intercept

1.774** (0.119)

1.369**

(0.102)

1.777**

(0.120)

0.968**

(0.105)

1.162**

(0.109)

Adjusted R²

0.239

0.293

0.264

0.310

0.368

Note: **parameter estimate is significant at the 1% level (p-value < 0.01); *parameter estimate is significant at the 5% level (p-value < 0.05). Numbers in parentheses are standard errors.

Source: ESS 2002/2003, author’s computations

 

 

Table 4A: Parameter estimates from separate ordinary least square regression analysis of exclusionism of immigrants,
 including interaction with age

Independent variables

Austria

(N=1559)

Germany

(N=2207)

Denmark

(N=1264)

Sweden

(N=1600)

UK

(N=1708)

Perceived welfare threat

0.384** (0.028)

0.459**

(0.025)

0.434**

(0.035)

0.558**

(0.032)

0.574**

(0.029)

Education

-0.028**

(0.006)

-0.024**

(0.005)

-0.041**

(0.006)

-0.024**

(0.005)

-0.023**

(0.005)

Age (ref: 26 - 55)

 

 

 

 

 

- 15 – 25

-0.572**

(0.223)

-0.583*

(0.260)

-0.036**

(0.268)

-0.024

(0.199)

-0.596**

(0.235)

- 56 +

0.406**

(0.160)

0.299*

(0.130)

-0.235

(0.166)

0.632**

(0.140)

0.382*

(0.153)

Welfare threat x younger age

0.117

(0.073)

0.116

(0.077)

-0.054

(0.089)

-0.019

(0.070)

-0.132

(0.070)

Welfare threat x older age

-0.091

(0.049)

-0.072

(0.038)

-0.072

(0.055)

-0.181**

(0.049)

-0.078

(0.045)

Male (ref. = female)

-0.007

(0.030)

0.052*

(0.025)

0.078*

(0.032)

-0.013

(0.027)

-0.070*

(0.029)

Income

-0.000003

(0.00001)

-0.00001

(0.00001)

-0.00001

(0.00001)

-0.00001

(0.00001)

-0.00001

(0.00001)

ISEI

-0.001

(0.001)

-0.003**

(0.001)

-0.001

(-0.001)

-0.003**

(0.001)

-0.002

(0.001)

Church attendance (ref.= never)

 

 

 

 

 

- once a month

0.157**

(0.038)

-0.046

(0.035)

-0.005

(0.062)

-0.081

(0.048)

-0.136**

(0.042)

- rarely

0.139**

(0.038)

-0.034

(0.027)

0.058

(0.034)

0.015

(0.029)

-0.032

(0.032)

Intercept

1.745** (0.133)

1.312**

(0.116)

1.683**

(0.139)

0.799**

(0.118)

1.112**

(0.129)

Adjusted R²

0.242

0.294

0.263

0.316

0.371

Note: **parameter estimate is significant at the 1% level (p-value < 0.01); *parameter estimate is significant at the 5% level (p-value < 0.05). Numbers in parentheses are standard errors.

Source: ESS 2002/2003, author’s computations

 

Table 5A: Selected country-level characteristics

Country

Proportion of non-Western[24] non-nationals in population (2000)[25]

Average annual number of asylum applications per 1,000 capita (2001-2002)[26]

Average annual net migration per 1,000 capita (1995-2000)[27]

Unemployment rate (2002)[28]

Austria

10.2 %

4.27

0.6

4.2 %

Germany

6.1 %

1.09

2.3

8.2 %

Denmark

4.9 %

1.73

2.7

4.6 %

Sweden

7.7 %

3.18

1.0

4.9 %

UK

3.4 %

1.89

1.6

5.1 %

Source: Different sources; see the footnote

 

The highest proportion of non-Western non-nationals in the total population can be found in Austria (10.2%), followed by Sweden (7.7%) and Germany (6.1%). In Denmark and the United Kingdom, the proportion of non-Western non-nationals in the population (4.9%, 3.4% respectively) is the lowest among those five countries. Austria also receives the highest average number of asylum application per year (4.27), assessed per 1,000 inhabitants. The second country with the highest number of asylum seekers is Sweden with 3.18 asylum applications per 1,000 capita per year. Those countries are followed by the United Kingdom with 1.89 asylum applications and Denmark with 1.73 asylum applications per 1,000 capita per year. Germany has the lowest yearly number of asylum seekers per 1,000 inhabitants among all those countries. However, Germany and Denmark are countries with the highest yearly net positive migration per 1,000 inhabitants (2.3, 2.7). The United Kingdom follows with 1.6 immigrants and Sweden with 1 immigrant per 1,000 capita per year. Austria has the lowest number of immigrants per 1,000 capita per year (0.6). Finally, Germany has rather high unemployment rate (8.2%) compared to the other countries, where the unemployment is on a similar level: 5.1% in the United Kingdom, 4.9% in Sweden, 4.6% in Denmark, and 4.2% in Austria.

 

 

A2. Annex 2: Items measuring the key concepts (ESS 2002/2003 questionnaire)

 

Exclusionism of immigrants

(1) To what extent do you think (country) should allow people of a different race or ethnic group as most (country) people to come and live here?[29]

(2) To what extent do you think (country) should allow people form poorer countries in Europe to come and live here?

(3) To what extent do you think (country) should allow people from poorer countries outside Europe to come and live here?

The reliability of the scale exclusionism of immigrants is high in all the countries (Cronbach alpha higher than 0.9).

 

Perceived welfare threat

(1) Would you say that people who come to live here generally take jobs away from the workers in (country) or generally help create new jobs?

(2) Most of the 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?

(3) Would you say that it is generally bad or good for (country)’s economy that people come to live here from other countries?[30]

(4) How much do you agree or disagree that average wages and salaries are generally brought down by people coming to live and work here?

(5) How much do you agree or disagree that people who come to live and work here generally harm the economic prospects of the poor more than the rich?

The reliability of the scale perceived welfare threat is good: Cronbach alpha is 0.7 in Austria, Denmark and Sweden and 0.8 in Germany and the United Kingdom.

 

 

A3. Annex 3: Definition of immigrants´ generations and the native population in the sample

 

In scientific literature, the immigrants´ generations are usually defined as follows: first generation immigrants are those who came to live in a country but they were born in another country (Saucedo, White, Glick, 2003; Fertig, Schmidt, 2001), 1.5 generation immigrants are defined as those who immigrated in a country with their parents in their early life, and grown up there (Choi, Cranley, Nichols, 2001), second generation immigrants are those who were born in the country their parent(s) immigrated into (Strelitz, 2004; Saucedo, White, Glick, 2003; Choi, Cranley, Nichols, 2001; Fertig, Schmidt, 2001). Ramakrishnan (2004), giving the example of the immigrants into the United States, claims that in most studies those who were born in the U.S., and at least one of their parents were born outside the U.S are also defined as second generation immigrants. However, the author labels those as the 2.5 generation immigrants. The third generation immigrants are the descendants of the second generation (Ramakrishnan, 2004; Choi, Cranley, Nichols, 2001).

            To find an explicit definition of the “native” is rather difficult and in the scientific studies they are often contrasted to the immigrants´ generations mentioned above. In the paper, I use a term “native population” to refer to those who are not the first, 1.5, and second generation immigrants, thus to those who were born in the respective country and at least one of their parents as well. I do not include the second generation immigrants, because even if they were born in the country their parents immigrated into, they are often raised in the immigrants´ communities, they might perceive themselves as immigrants, and they are often perceived as immigrants by the non-immigrant population. Ireland says about the immigrants from Southern Europe to Western Europe: “Due to persistent discrepancies between Southern Europeans´ socioeconomic, cultural, and political situation and that of the native stock residents, even second- and third- generation Italians, Iberians, and Greeks have been considered part of the immigrants-origin population, notwithstanding their ancestral homelands´ membership in the European Union and new status as countries of immigration on their own right” (Ireland, 2004: 2). I think this idea can be broadened also to other groups of immigrants in Western Europe, even if there are undoubtedly differences between the immigrants´ groups of different origin. Whether the exclusionism of immigrants among the population of immigrant origin is stronger, or weaker, or the same as among the population of non-immigrant origin is disputable, but it is behind the scope of the present research to deal with this question.

 

 

References

 

Other online sources:

 

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[1] Geddes (2003a: 17) recognizes the primary migration between 1950s and the beginning of 1970s with workers invited to help with European economic reconstruction, followed by family migration for the purpose of family reunification with those workers, and finally, asylum and illegal migration accelerated in the 1990s, as the three main periods of immigration into Europe.

[2] Wallace (1995: 5) defines xenophobia as a reaction to foreigners, while racism as a reaction to a generic group which have been racialised.

[3] In the choice of the countries for comparison also the data quality was taken into account.

[4] http://ess.nsd.uib.no/2003_Fworksummary.jsp

[5] Final report: Sampling for the European Social Survey, http://www.europeansocialsurvey.org/

[6] Weighting European Social Survey Data, http://ess.nsd.uib.no/2003_documentation.jsp

[7] See Annex 3A for more information about the definition of the immigrants´generations and the native population.

[8] The items forming the key scales as well as their reliability coefficients are presented in the Annex A2.

[9] The only exception is Sweden where less than half of the respondents perceived the immigrants having different race or ethnic origin.

[10] Age is recoded into three categories, 15-25, 26-55, 56+, since the relationship with perceived welfare threat is not linear and thus cannot be included in OLS regression. Moreover, I want to separate the effects for the categories of the population in education, working population and the older population that tend to be more dependent on the social security (the actual retirement age in Europe is often below 60).

[11] Measured in years of total education

[12] Due to the large number of missing data on income in the data set in most of the countries (36% in Austria, 21% in Germany, 16% in the United Kingdom, 14% in Denmark and 6.5% in Sweden), the missing values are replaced with the mean income of the countries in order to avoid loosing too many cases for the regression analysis. Mean imputation can be problematic because it decreases the variance, and thus low significance levels are reached more easily. However, in the regression analysis, I checked for the differences in the results both with the original variable and with the variable with replaced missing values and the results did not differ markedly.

[13] ISEI was created using a conversion tool of Ganzeboom and Treiman (1996b) that allow converting the ISCO-88 Standard Occupational Classification into International Socio-Economic Index of Occupational Status. This index can be perceived as “measuring the attributes of occupations that convert person’s education into income” and it is measured on a scale from 16 to 90 (Ganzeboom, Treiman (1996a).

[14] I wanted to control for religious affiliation but there is high non-response on this variable and some religious denomination are not represented in some countries while they are very common in the others (e.g. in Sweden there are no Catholics in the sample). Thus, I chose to control for church attendance; this variable has three categories: going to church at least once a month (1), rarely (2), never (3)

[15] Those characteristics for the selected countries are presented in the Annex, Table 5A

[16] Unemployment is strongly correlated with number of asylum applications (-0.752, p<0.001) and dummy variable for Germany (0.982, p<0.001); proportion of immigrants is strongly correlated with net migration (-0.705, p<0.001), asylum applications (0.807, p<0.001) and dummy variable Austria (0.805, p<0.001); number of asylum applications is strongly correlated with net migration (-0.973, p<0.001) and dummy variable Austria (0.812, p<0.001). 

[17] Berry and Feldman (1985: 41) warn that the main consequences of multicollinearity are wide confidence intervals for coefficients estimates and small t-statistics for significance tests. Moreover, it is not possible to precisely separate the effects of the independent variables that are strongly correlated in one regression equation.

[18](1) To what extent do you think (country) should allow people of a different race or ethnic group as most (country) people to come and live here?; (2)…allow people of a same race or ethnic group as most (country) people…?; (3)…allow people form richer countries in Europe…?; (4)…allow people from poorer countries in Europe…?; (5)…allow people from richer countries outside Europe…?, (6)…allow people from poorer countries outside Europe…? (Note: items in italics were chosen).

[19] The coefficient is computed by substituting the values in the regression equation 2: a + ß1. The coefficients for the rest of the countries are computed in in a similar way using the approriate coefficients; the coefficient for the UK corresponds to the intercept (according to Hardy, 1993).

[20] Those results are not shown in Table 4; they are obtained when changing the reference category in the equation 2.

[21] The coefficient is computed by substituting the values in the regression equation 2: ßPWT + ß5. The coefficients for the rest of the countries are computed in in a similar way using the approriate coefficients, the coefficient for the UK corresponds to ßPWT (according to Hardy, 1993).

[22] Only the interactions that were statistically significant at least at one of the compared countries are shown.

[23] The interaction between age and perceived welfare threat explains additional 6% of the variance of the exclusionism of immigrants.

[24] Citizens of countries except for EU-15 countries, EFTA countries, USA, Canada, Australia and New Zealand (Coenders, Lubbers, Scheppers, 2003b: 86)

[25] Source: Eurostat, Office for National Statistics (UK), Statistisches Bundesamt (Germany) in Coenders, Lubbers, Scheppers (2003b: 86)

[26] Source: UNHCR and Eurostat in Coenders, Lubbers, Scheppers (2003b: 86)

[27] Source: UN Population Division (2002). Net migration is the annual number of immigrants less the annual number of emigrants (including both citizens and non-citizens). The rate is computed as the net number of migrants, divided by the average population of the receiving country, expressed per 1,000 population of the country. http://www.unpopulation.org

[28] Source: Eurostat (2002). The unemployment rate is the proportion of unemployed persons in total labour force. http://epp.eurostat.cec.eu.int/

[29] The answer was recoded as follows: 4=allow many to come and live here; 3=allow some; 2=allow a few; 1=allow none.

[30] Items 1 to 3 were recoded from the 11 point scale into the 5 point scale in order to allow combining them with items 4 and 5 that were measured on the 5 point scale.