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Asian Journal of Political Science

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Attitudes toward immigrants and immigrationpolicy in Asia and the Pacific: a quantitativeassessment of current theoretical models beyondwestern countries

Joan Barceló

To cite this article: Joan Barceló (2016): Attitudes toward immigrants and immigration policy inAsia and the Pacific: a quantitative assessment of current theoretical models beyond westerncountries, Asian Journal of Political Science, DOI: 10.1080/02185377.2015.1136228

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Attitudes toward immigrants and immigration policy in Asiaand the Pacific: a quantitative assessment of currenttheoretical models beyond western countriesJoan Barceló

Department of Political Science, Washington University in St. Louis, St. Louis, MO, USA

ABSTRACTThis article empirically assesses the validity of current theoreticalmodels of attitudes toward immigrants and immigration policy inthe Asia-Pacific region. This paper takes representative data fromthe World Values Survey and implements a multilevel model totest five of the main theories in the literature: the human capitaltheory, the social capital theory, the political orientation theory,the contact/group threat theory and the economic competitiontheory. The results from the analysis lend credence to theimportant effects of human capital, social capital and political-ideological variables on respondents’ attitudes toward immigrantsand immigration policy. However, the results provide mixed andweak evidence for the contact/group threat theory and the role ofeconomic determinants. Importantly, economic determinants tendto be more powerful in shaping people’s attitudes towardimmigration policy than shaping attitudes toward immigrants aspeople. Altogether, this article sheds new light on the validity ofcurrent theoretical models based on western countries for otherareas of the world. Finally, the results from the paper also supportthe usefulness of non-economic, as opposed to purely economic,models in the understanding of individuals’ attitudes towardimmigrants and immigration policy in the Asia-Pacific region.

KEYWORDSImmigration; Immigrants;Attitudes; Prejudice;Discrimination; Survey; PublicOpinion

Introduction

By mid-2013, the number of international immigrants was estimated at approximately 214million people (UN Population Division, 2013). Even though migratory flows occur bothacross and within national boundaries, international migrants face numerous obstaclesbecause of restrictive immigration regimes and strong societal opposition by host societies(Messina, 2007). Studies on the sources of negative attitudes toward immigrants havelargely focused on the European continent or the Organization for Economic Cooperationand Development (OECD) countries (e.g. Gang et al., 2002; Lahav, 2004; Coenders et al.,2005; Kessler and Freeman, 2005; Semyonov et al., 2006; Martínez-Herrera and Moualhi,2007; Ceobanu and Escandell, 2008; Malchow-Moller et al., 2008; Meuleman et al., 2009;Rustenbach, 2010; Martínez-Herrera et al., 2013). Heterogeneity within the continent(Zick et al., 2008) and availability of high quality data (e.g. Eurobarometer, European

© 2016 Taylor & Francis

CONTACT Joan Barceló [email protected]

ASIAN JOURNAL OF POLITICAL SCIENCE, 2016http://dx.doi.org/10.1080/02185377.2015.1136228

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Social Survey (ESS)) are the main reasons for this geographical specialization (Ceobanuand Escandell, 2010). Current theoretical models are based on a limited number ofwestern countries, even though they are generally offered as universally applicable. Thepurpose of this article is to expand this research line to countries at different stages ofdevelopment and migration histories that we encounter in the Asia and the Pacific region.

The stock of international migrants in the Asia-Pacific region constitutes 1.3 per cent ofthe total population in the region, which amounts to about 53 million people. Even thoughthis percentage is substantially lower than the average number of immigrants hosted insome European countries, about one-quarter of the total number of international migrantsin the world is located in Asia and the Pacific. The region is complex and diverse. Somecountries have nearly no immigration, such as Vietnam—with a population with 0.08per cent non-citizens and international refugees—and some other countries have alarge stock of international immigrants, such as Singapore—with 38.2 per cent foreign-born population (UN Population Division, 2013).1

Altogether, the heterogeneity in the region presents an excellent setting to test the arrayof explanations that researchers have provided for OECD member states to explain thedevelopment of anti-immigrant attitudes and policies in the Asia-Pacific countries:human capital, political orientation, social capital, contact (or group threat theory) andeconomic competition theory. I take the World Values Survey (WVS), conducted duringthe period between 2005 and 2008, to explore individual and country-level economic andnon-economic determinants of attitudes toward immigrants and immigration policy.

This article makes several contributions to the study of natives’ attitudes. First, thisstudy provides an overview of the main theoretical models that are susceptible to beimported to the Asia-Pacific region. Second, it takes into account methodological com-plexities with the incorporation of different weighting procedures that may have biasedthe results. Finally, this paper also accounts for theoretical and empirical discrepanciesbetween the two dependent variables that are generally used in the literature: attitudestoward immigrants (as people) and openness to immigration (as policy).

The article proceeds as follows. The first section briefly describes the main theories thatexplain attitudes toward immigrants and immigration in other parts of the world, andwhich constitute the theoretical hypotheses of the analysis. The second section detailsthe data, the research method, and the operationalization of the independent and depen-dent variables. The third section presents the main empirical results. The final section dis-cusses the main findings, the theoretical and policy implications and avenues for furtherresearch.

Theoretical background

There are two types of attitudes on the issue: views toward immigrants and views towardimmigration policy (Ceobanu and Escandell, 2010). Even though most researchers chooseto study them together (e.g. Berg, 2010; Burns and Gimpel, 2000; Dovidio and Esses, 2001;Luedtke, 2005; Segovia and Defever, 2010), this practice may invalidate the measure giventhat they tap into different theoretical considerations. However, I do expect both attitudesto arise from a similar set of beliefs, values and opinions. This common source justifies theuse of explanatory models based on the same theoretical structure for both dimensions.For the most part, the theoretical differences between the two constructs generally

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attribute a stronger degree of ethno-racial prejudice when explaining generalized opposi-tion to immigrants rather than opposition to the policy. By contrast, orientations towardthe policy tend to be associated more strongly with perceptions about the economic andsocial consequences of an influx of immigrants for the entire country. The literature onattitudes toward immigrants and immigration policy preferences has provided anumber of explanations for negative attitudes toward immigrants and immigration (seee.g. Ceobanu and Escandell, 2010; Zamora-Kapoor et al., 2013). The most prevalent ofthem are the human capital theory, the social capital theory, the political orientationtheory, the contact/group threat theory and the economic competition theory.

The Human Capital Hypothesis proposes that higher educational attainment reducesanti-immigrant attitudes and increases the ideal level of immigration in the country(e.g. Gang et al., 2002). Two sorts of theoretical argument for this effect can be differen-tiated: labour-related and non-labour-related arguments. The former suggests that edu-cation provides the skills to the members of the host society to avoid competing forjobs against immigrants in the labour market. Additionally, educated people benefitmore from the low wages paid to unskilled immigrants. The latter asserts that educationis understood as increasing reflexivity and open-mindedness, which is supposed to leadeducated people to have higher levels of tolerance toward racially or culturally differentpeople. Even though some authors have taken education as a proxy for worker’s skills(Mayda, 2006), when both dimensions have been tested against each other, non-labourarguments account for most of the variance of the relationship between educationalachievement and attitudes toward immigrants (Hainmueller and Hiscox, 2007).

The Social Capital Hypothesis is based on the idea that those who possess high levels ofsocial capital are more likely to respect the rights of others and be more tolerant towarddifference (Putnam, 2001; Herreros 2008; Herreros and Criado, 2009). Social capital canbe defined as the set of ‘features of social organization such as networks, norms, and socialtrust that facilitate coordination and cooperation for mutual benefit’ (Putnam, 1995: 67).Therefore, individuals with high levels of social capital will tend to expect strangers to bemore trustworthy, regardless of the cultural background of the others. And so it seemsreasonable to expect these individuals to be more accepting of international immigrants(Herreros and Criado, 2009). Following this rationale, the empirical strategy focuses onthe individual social capital rather than on the aggregate social capital.

Another potential source of anti-immigrant and anti-immigration attitudes comesfrom individuals’ political-ideological orientation. Those people with low political interestmay be willing to blame others for societal misfortunes, and immigrants are an easy target(Espenshade and Hempstead, 1996). Yet it could also be the case that those with relativelylow political interest also lack political information and, therefore, the tools to assess theactual impact of immigration on society. Additionally, negative attitudes toward immi-grants have been linked to rightist political movements, especially in Europe with theemergence of right-wing parties that push for stricter controls over immigration, andhave become more politically powerful in the last decades (Sides and Citrin, 2007).Related to the ideological spectrum explanations, some authors argue that nationalistattitudes, defined as those who express feelings of national superiority over others,tend to discriminate against immigrants (De Figueiredo and Elkins, 2003; Raijmanet al., 2008).

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In a more complex way, the contact hypothesis proposes that under conditions of equalstatus, common objectives, authority sanction and the absence of competition, interactionbetween two groups should lead to more positive attitudes between them (Allport, 1954;Pettigrew and Tropp, 2006; Paluck and Green, 2009). As regards the attitudes towardimmigrants, it is unlikely that the benign effects of contact ever happen since the fourrequirements are rarely met simultaneously. Therefore, in its negative version, thistheory is sometimes presented as the group threat or group position theory (Blumer,1958; Hainmueller and Hangartner, 2013; Quillian, 1995).

In the group threat theory, members of the dominant group consolidate their superiorposition through prejudice toward the subordinate group and foster a clear in-group/out-group differentiation. When people come into contact with immigrants in the presence ofcompetition for scarce resources, intergroup hostility should be expected. As the require-ment for the beneficial effects of intergroup contact is rarely realized, this paper takes thegroup threat side of the contact hypothesis to argue that as the size of the minority groupincreases, especially if it occurs quickly, the feeling of threat by the majority will increaseand they will feel they may have to compete for cultural hegemony (Hopkins, 2010).

Finally, economic competition is a commonly analysed source of negative attitudestoward immigrants and immigration. This theory postulates that the more an individualis exposed to direct competition for scarce material resources, the more discriminationtoward the rival out-group it will foster (Mayda, 2006). While the contact hypothesislinks the size of the immigrant population to group threat through the competition forcultural hegemony, the economic competition theory hypothesizes that the source ofprejudice is the dispute over material resources. At the individual level, low-skillednative workers who enter into competition with low-skilled immigrants are expected tobe more strongly against immigrants and immigration (Scheve and Slaughter, 2001).For similar reasons, individuals’ employment status might be a potential determinantsince an unemployed respondent might tend to blame immigrants for their unemploy-ment (Rustenbach, 2010). As a consequence, those low-skilled native workers, unem-ployed or with low family income, are expected to compete more directly for economicresources with immigrants and, consequently, to hold more negative attitudes towardimmigrants and immigration. In conjunction with individual determinants, macro-econ-omic factors may also play a role in shaping natives’ attitudes. Alterations in the state ofthe economy, unemployment rates, or the economic prosperity of the country mightchange the feeling of threat of the native population vis-à-vis immigrants (Coenderset al., 2008; O’Rourke and Sinnott, 2006). At the same time, a country’s high levels ofinequality may lead to fiercer competition between low-skilled native workers and immi-grants because the lower strata has a smaller portion of the national product to share and,therefore, more is at stake in the battle between native and immigrant population.

Methodology: data and measurements

Data

To test the relative importance of the theories in the Asia-Pacific region, I use data fromthe World Values Survey (2005–2008 period) (World Values Survey Association, 2013).The WVS is a global research project that explores people’s beliefs and values and is

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the most widely used worldwide survey centre for research in the social sciences. Certainly,WVS, ESS, International Social Survey Programme, and all other international surveyagencies have been criticized. The most prevalent critique is the assumed comparabilityof cross-national survey measurements (Davidov et al., 2014). However, it is also truethat these data sources, and also the WVS, remain the main source of survey dataaround the world and the source of a number of influential works in the discipline aslarge, and in research on attitudes toward immigrants in particular (e.g. Ceobanu andEscandell, 2010; Mayda, 2006; Strabac and Listhaug, 2008). In particular with the WVS,the breadth of countries surveyed has made this cross-national survey data a standardresource for studying variation of political attitudes across countries around the world.

Wave 5 of the WVS included representative survey data for 11 of the Asian-Pacificcountries as classified by the regional activities of the United Nations: Australia (1,421interviews in 2005), China (1,991 interviews in 2007), Georgia (1,500 interviews in2008), India (2,000 interviews in 2006), Indonesia (1,000 interviews in 2006), Japan(1,000 interviews in 2005), Malaysia (1,200 interviews in 2006), South Korea (1,200 inter-views in 2005), Thailand (1,500 interviews in 2007), Turkey (1,346 interviews in 2007) andVietnam (1,584 interviews in 2006), with a total of 15,742 valid respondents. The sampleof countries available from the region is representative of the geographical area.

Empirical specification

The empirical strategy should take into account the hierarchical nature of the data whereindividual data are grouped within countries. Multilevel models are a commonly usedmethod and an excellent way to address contextual determinants of individual behaviour(Gelman and Hill, 2007) when independent variables are located at both individual (e.g.respondent’s age) and country level (e.g. stock of international immigrants at countrylevel). Even though limitations of the minimum sample size of 50 groups (level 2) are adifficult hurdle to overcome with the current availability of data (Maas and Hox, 2005),the alternative of setting the group level variance to 0 or infinity seems worse (Gelman,2007). In this case, the number of second-level groups is 10 and 11 for the dependent vari-ables of attitudes toward immigrants and large-scale immigration respectively. Yet, somerelevant control and independent variables are missing for some countries in the sample,so models are replicated several times to capture the benefits of the trade-off betweencountries in the sample with valid values, and so the number of observations at level 1and 2, and the number of variables included in the models.

The modelling structure chosen to test my empirical hypothesis is a varying-interceptmodel with individual-level and country-level covariates. Thus, the hierarchical structureof the data has two levels, with individuals nested within countries. More complex models(varying-intercept and varying-slopes models) were too unreliable to be implemented dueto the small number of groups available for some models. More formally, this is the mod-elling specification implemented in the empirical section:

Level 1: Pr(Immigrants or Immigration policy)ij

= logit−1(b0j + b1X1ij + b2X2ij + . . .+ bkXkij)

Level 2:b0j = g00 + g01W1 + g02W2 + . . .+ g0MWM + u0j


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In the above equations, the βs are individual-level regression parameter, where β0j is theintercept of the country of the respondent. The γs are group-level regression parameterestimates.

Weighting procedure

A methodological issue that appears in the multilevel analysis refers to the weightingmethod of countries. If models are left unweighted, each country is weighted for the equiv-alent of its sample size. Since sample size is based on the specific survey design, and not onsubstantive criteria, weights based on sample size are inappropriate constructions. Tosolve this weighting issue, I complement the unweighted results with two different weight-ing strategies. First, I construct a model that represents the total population of the regionunder study. In this case, each country is weighted by its population size. Second, I con-struct a model that equally represents each country in the region. With the aim to providethe most complete analysis on the attitudes toward immigrants and immigration in theAsia-Pacific region, the three sorts of analyses are explored: unweighted models (sup-plementary information), weights by population size (supplementary information) andequal-sized models (reported in the paper). Since this paper’s aim is to make inferencesacross all countries in the region, the latter weighting strategy is the strategy presentedthroughout the paper.

Measurements and empirical hypotheses

In this paper, I link each theory to a set of independent variables to test the validity of someof the main theories in the literature. My outcome of interest is generalized animositytoward immigrants and immigration policy preferences. Given that the WVS provides ameasure for each of them, my empirical test analyses the factors that affect both separately.The first dependent variable refers to attitudes toward immigrants. This is a dummy thattakes the value of 1 if, given a list of societal groups, immigrants/foreign workers are men-tioned as a group that the respondent would not like to have as neighbours. Otherwise, ittakes the value of 0.2

The second dependent variable captures attitudes toward immigration policies. Theoriginal wording is the following:

How about people from other countries coming here to work. Which one of the following doyou think the government should do? a) Let anyone come who wants to? b) Let people comeas long as there are jobs available? c) Place strict limits on the number of foreigners who cancome here? d) Prohibit people coming here from other countries? e) Don’t know.

To make this variable comparable to the first dependent variable, I recode it to take thevalue of 1 if the respondent chooses either a or b, and 0 if c or d is chosen instead. Thee choice is left as a missing value.

The first hypothesis that comes to explain natives’ attitudes toward immigrants andimmigration is the human capital theory. There are two potential variables that mightcapture this same underlying concept: total number of years of formal schooling ofmembers in host societies and a set of categorical values of educational attainment. Theformer tends to perform better as a predictor of these attitudes toward immigrants

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(Hainmueller and Hiscox, 2007). Therefore, education is operationalized with two dummyvariables: secondary education, which takes the value of 1 if the highest educational attain-ment is secondary education, and 0 otherwise; and tertiary education, which takes thevalue of 1 if the highest educational attainment is at the tertiary level, and 0 otherwise.Primary education is the category of reference.

The second hypothesis is the social capital theory. This is formed by two dimensions:social trust and involvement in social organizations. Social trust is measured with the fol-lowing question: ‘Generally speaking, would you say that most people can be trusted orthat you need to be very careful in dealing with people?’, which takes as a dummy variablebetween trusters (1) and not trusters (2). The latter is measured by the number of organ-izations in which the respondent is involved. This is asked as follows:

Now I am going to read off a list of voluntary organizations. For each one, could you tell mewhether you are an active member, an inactive member or not a member of that type oforganization?: membership of church or religion organization; sport or recreational organiz-ation; art, music, educational organization; labour union; political party; environmentalorganization; professional association; charitable/humanitarian organization; consumerorganization or any other organization.

An index that sums the value of 0 for not being a member of the organization, 1 for beingan inactive member and 2 for being an active member is created. The index ranges from 0(not a member of any type of organization) to 20 (active member of all types of organiz-ation). Even though both are usually understood to measure social capital, the interperso-nal trust dimension captures better the theoretical meaning of trust with strangers. Thus, itis expected to have a stronger effect.

The third hypothesis is the effect of political orientation. The first measurement refersto the potential effect of interest in politics. Two dummy variables for the position of some-what interested and very interested have been created. The category of reference is gener-ated by those who express themselves not to be very interested or not at all interested inpolitics. I use dummies to avoid since I do not necessarily expect a linear and equidistancerelationship among categories. Secondly, ideology is measured with a standard ideologicalself-placement question This scale is a continuous variable that ranges from the far left (0)to the far right (9). However, this hypothesis will not be tested for China and Malaysiasince it is not available. Finally, national pride is measured with the following question:‘How proud are you to be [nationality]? Very / Quite / Not very / Not at all proud’,using a dummy, which takes the value of 1 if the respondent is very proud of their ownnationality, and 0 otherwise. The categorization into a dummy of this variable is motivatedby the lack of variability in the data across individuals. In particular, less than 9 per cent ofthe sample reports feeling not very proud or less of their nationality. Therefore, to makethe coefficient stable, I decide to collapse the three lowest categories into a single categoryby creating a dummy that differentiates between those who report being very proud (58per cent of the sample) and all other categories (42 per cent of the sample).

The contact or group threat hypothesis is operationalized in two ways. First, I take intoaccount the stock of international immigrants in a country as a percentage of the totalpopulation (in 2008). Second, I introduce a measure of the recent pace of immigration.There are reasons to believe that recent increases in the net migration rate, calculated asthe difference between emigrants and immigrants divided by 1,000 units of population,


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might be more relevant than the stock of already settled immigrant population. As thesample includes countries with a significant recent migration history as well as countrieswith a low rate of recent immigration, the rapidly increasing size of the immigrant popu-lation might increase natives’ perceived threat. To capture this, the annual average netmigration rate for the period 2003−2008 is included in the analysis. Even though thenumber of immigrants naturally increases the likelihood of contacts between nativesand immigrants, this measure most likely captures the defensive reaction of nativeswho view immigrant out-groups as a threat to the natives’ dominant position. Thismeasurement is quite standard and follows previous work from this theoretical framework(Blumer, 1958; Hainmueller and Hangartner, 2013; Quillian, 1995).

Finally, economic competition is measured at two levels: at the individual and at thecountry level. From an individual level, the first variable to consider is the relativeincome scale. This divides the population in 10 steps of family income, from low (0) tohigh (9), standardized by country in order to make it comparable cross-nationally. Thesecond dimension that might capture economic competition is whether the respondentis a skilled worker or not. This variable takes the value of 1 if the respondent is anemployer/manager, professional worker, office worker, foreman or supervisor or skilledmanual worker, and 0 otherwise. In these cases, competition with immigrants is expectedto be relatively lower. And it takes the value of 0 if the respondent is a semi-skilled orunskilled manual worker, an agricultural worker, a farmer who owns his own farm, amember of the armed forces, employed in security, or has never had a job. In thesecases, competition is expected to be relatively high. Other jobs are taken as missingvalues.3 Lastly, employment status is measured with a dummy that takes the value of 1if the respondent is employed, and 0 otherwise. Another dummy takes into accountwhether the individual has been employed in the last five years (1) or not (0).

At a country level, the perceived economic competition is measured by using severalstatic indicators: national unemployment rate (in 2008), gross domestic product percapita (in logarithmic scale, in 2008), and dynamic indicators of economic conditions:average annual unemployment rate in the last five years (between 2003 and 2008) andaverage annual change of gross domestic product in the last five years (between 2003 and2008). Lastly, the measure of country inequality is the Gini coefficient (in 2008). Eventhough these measures are not ideal for the theory of economic competition, theyfollow the standard approach for operationalizing perceived economic competition (e.g.Coenders et al., 2008; Coenders and Scheppers, 2008; Strabac and Listhaug, 2008).

To summarize the linkage between theory and measurements and my empirical expec-tations, Table 1 reports the variables that correspond to each theory and the hypothesizeddirection of the effects. Notice that the set of theories that are meant to explain one depen-dent variable is the same set of theories that are meant to explain the other dependent vari-able. Therefore, I jointly report the expectations for both, although the empirical resultswill be provided for each variable separately.

Results

Country-level surveys suggest an extreme cross-national variation in natives’ attitudestoward immigrants and immigration. Figure 1 shows that there are four types of countries.First, tolerant countries are those with tolerance levels above the mean of the sample

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regarding both immigrants and immigration, such as Australia (19 and 27 percentagepoints, respectively) or China (11 and 12 percentage points, respectively). Second, intoler-ant countries are those countries, such as Malaysia (−30 and −25 percentage points,respectively) or Thailand (−18 and −11 percentage points, respectively), which havelevels below the mean in both indicators. Third, reluctant acceptant countries are thosethat may not like immigrants but would rather have a more permissive immigrationpolicy, such as Vietnam or South Korea. And, finally, friendly antagonist countries arethose countries which are tolerant toward immigrants but hold a restrictive viewtoward immigration, as occurs in Georgia.

Table 1. Summary of theoretical hypotheses and their operationalization.Theories Indicators (expected sign on positive attitudes)

Human Capital Hypothesis Educational attainment (+)Social Capital Hypothesis Social trust (+)

Involvement in social organizations (+)Political–Ideological Hypothesis Interest in politics (+)

Left–right ideological placement (−)National pride (−)

Contact Theory / Group Threat Stock of international immigrants, 2008 (−/+)Migration rate, 2008 (−/+)

Economic Competition Relative income scale (+)Skilled worker (+)Employment status (−)National unemployment rate, 2008 (−)Average annual unemployment rate, 2003–2008 (−)GDP per capita, log scale, 2008 (+)Average annual growth of the GDP per capita, 2003–2008 (+)Gini coefficient, 2008 (−)

Italics indicate country-level variables.

Figure 1. Observed values of positive attitudes towards immigration by country.


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However, observed values in tolerance levels might conceal huge cross-national hetero-geneity that may drive the results. Unequal levels of human capital, social capital, politi-cization of immigration, different features of immigration or the state of the economy,have been regarded as potential explanations of cross-national differential attitudestoward immigrants and immigration in the Asia-Pacific region. The validity of each argu-ment is empirically tested and separately analysed in this section by using several modelspecifications.4 Tables 2 and 3 report the results of attitudes toward immigrants (as people)and immigration (as policy) with equally weighted countries, respectively. Columns inthese tables represent different model specifications (null model with no predictors, indi-vidual-level model with only individual-level predictors, model to test the contact theory,and model to test the economic competition theory). In particular, since the number ofcountries in the sample is small, I need to test each hypothesis involving country-level pre-dictors separately to ensure enough degrees of freedom per model. The empirical analysisis conducted in such a way that I test as many theories as possible to as many countries aspossible. This is done by gradually removing those variables from the model that aremissing for entire countries. In particular, the first four columns from the tables showthe results of all countries with valid responses in all variables (altogether, six countries).The following three columns show the results of all countries with valid responses in allvariables except the variable immigrant and size of the town of residence (eight countriesfor the model of immigrants from Table 2, and nine for the policy model from Table 3).And, finally, the last three columns show the results of all countries with valid responsesfor all variables except for the variable of immigrant, size of the town of residence, andleft−right ideological self-placement (10 countries for the immigrants model from Table2, and 11 for the policy model from Table 3).

Human capital hypothesis

The human capital hypothesis is tested by looking at the impact of the highest educationallevel on individual’s attitudes toward immigrants and immigration. Tables 2 and 3, and A1−A6 in the Appendix, indicate a consistent relationship between having received second-ary or tertiary education versus holding a primary degree and having positive attitudestoward immigrants and the inflow of immigrants. Even though the reliability of the esti-mates varies by models, the direction is consistent throughout all the models (completepooling, no pooling, and all models for the three weighting procedures) for both immi-grants and immigration policy.

Figure 2 plots the predicted probabilities of attitudes toward immigrants and immigra-tion policy at different levels of the highest educational attainment for the selectedcountries when using the full models with countries equally weighted (Table 3). After con-trolling for all the first- and second-level variables of the model, an average respondentwith primary studies, or less, holds positive attitudes toward immigrants with a probabilityof 62.5 per cent. This likelihood for an individual with the same personal characteristicsand from a country with the same indicators would increase to 66.1 per cent and 67.8per cent with secondary and tertiary education, respectively.

These results point to the relevant effect of education, as it is effectively increasingopen-mindedness and tolerance regarding racially and culturally different people, whichin turn translates into greater support for more open policies for the entry of new

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Table 2. Determinants of positive attitudes towards immigrants (countries equally weighted).

DV: Immigrants Null IndividualContacttheory

Economiccompetition Full Individual

Contacttheory


Contacttheory

Economiccompetition Full

IV Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff.

Sex −0.04 -0.04 -0.04 -0.04 0.00 -0.01 0.00 0.00 0.01 0.01 0.01 0.01Age 0.02* 0.02* 0.02* 0.02* 0.01 0.01 0.01 0.00 0.00 0.00 0.00 0.00Age square 0.00* 0.00* 0.00* 0.00* 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Size town 0.05*** 0.05*** 0.06*** 0.06***Immigrant 0.24 (.14) 0.26 (.12) 0.19 0.19Education secondary −0.12

(.13)−0.10(.19)

−0.08 −0.09 0.13* 0.12* 0.12 (.11) 0.11 0.16*** 0.15*** 0.15*** 0.15***

Education university 0.03 0.04 0.07 0.06 0.27*** 0.25*** 0.26*** 0.22** 0.23*** 0.23*** 0.23*** 0.23***Truster 0.30*** 0.31*** 0.30*** 0.30*** 0.34*** 0.34*** 0.34*** 0.35*** 0.27*** 0.27*** 0.27*** 0.27***Social organization −0.03*** −0.03*** −0.04*** −0.04*** −0.02*** −0.02*** −0.02*** −0.03*** −0.01** −0.01** −0.01** −0.01**Somewhat interested −0.08 −0.10

(.12)−0.09 (.15) −0.09

(.15)−0.07 −0.08 −0.07 −0.06 0.04 0.04 0.05 0.04

Very interested −0.14* −0.14* −0.15* −0.15* −0.08 −0.08 −0.08 −0.04 −0.04 −0.04 −0.04 −0.04Left−right scale −0.03** −0.03** −0.03** −0.03** −0.07*** −0.07*** −0.07*** −0.07***Very proud ofnationality

−0.19*** −0.20*** −0.20*** −0.20*** −0.12** −0.12* −0.11* −0.08(.19)

−0.16*** −0.16*** −0.16*** −0.16***

Income −0.01 −0.01 −0.02 −0.02 0.02* 0.02 (.11) 0.02* 0.03* 0.02 (.11) 0.02 (.12) 0.02 (.11) 0.02 (.12)Skilled worker 0.10 (.12) 0.09 (.16) 0.09 (.13) 0.10 (.13) 0.17*** 0.17*** 0.18*** 0.19*** 0.14*** 0.13*** 0.14*** 0.13***Employment status 0.00 −0.03 0.02 0.01 −0.03 −0.03 −0.02 −0.02 −0.06 −0.08 −0.08 −0.08Constant 0.80** 0.97* 0.38 −8.13 3.01 0.99** 0.55* 16.18 1.23** 0.72** 0.36 −1.51 3.18

Random-effectsparametersIntergroup variancecomponent

0.64*** 0.62*** 0.01*** 0.00 0.00 0.50*** 0.03*** 0.13*** 0.00 0.61*** 0.36*** 0.29***

Stock of internationalimmigrants 2008

0.11*** 0.14** 0.11*** 0.09*** 0.09* 0.07 (.16)

Net migration rate2003−2008

−0.01(.10)

−0.01 (.15) 0.00 0.00

Nationalunemployment 2008

0.90 (.19) 0.03* 0.11

Unemployment rate2003−2008

−0.93 −0.09

(Continued )

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Table 2. Continued.



Contacttheory


Contacttheory



GDP per capita, logscale 2008

1.06*** −0.34(.18)

−0.66 0.50 (.13) −0.10

Growth of GDPpc,2003–2008

0.24** 0.03 −0.71 0.16

Gini coefficient, 2008 −0.04** −0.12* −0.02** −0.08* −0.04

Reliability estimate 0.99 0.99 0.59 0.00 0.00 0.99 0.85 0.96 0.38 0.99 0.99 0.99 0.99Log likelihood −9682.1 −4197.4 −9908.2 −9924.70 −9924.6 −5833.08 −5825.24 −5827.47 −13342.4 −9122.33 −9121.18 −9118.68 −9120.29Deviance 19364.3 8394.8 19816.4 19849.4 19849.3 11666.16 11650.48 11654.94 26684.82 18244.66 18242.35 18237.36 18240.58Number ofobservations

15433 7005 7005 7005 7005 9441 9441 9441 9441 14526 14526 14526 14526

Number of countries 10 6 6 6 6 8 8 8 8 10 10 10 10

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Table 3. Determinants of positive attitudes towards immigration policy (countries equally weighted).

DV: ImmigrationInflux Null Individual Contact theory

Economiccompetition Individual Contact theory


Individual(10)

Contacttheory

Modeleconomiccompetition Full model

IV Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff.

Sex −0.01 −0.01 −0.01 −0.04 −0.04 −0.04 −0.04 −0.07* −0.07* −0.07 −0.07*Age −0.01 −0.01 −0.01 −0.01 (.13) −0.01 (.13) −0.01 (.12) −0.01 (.11) −0.02** −0.02** −0.02** −0.02**Age square 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Size town 0.02 (.13) 0.02 (.13) 0.02 (.11)Immigrant 0.02 0.02 0.00Educationsecondary

0.03 0.03 0.04 0.05 0.06 −0.04 0.05 0.18*** 0.18*** 0.17*** 0.18***

Educationuniversity

0.15 (.11) 0.15 (.11) 0.14 (.13) 0.17** 0.17** 0.16* 0.16* 0.29*** 0.29*** 0.29*** 0.29***

Truster 0.33*** 0.33*** 0.33*** 0.35*** 0.35*** 0.34*** 0.35*** 0.36*** 0.36*** 0.36*** 0.37***Social organization 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02*** 0.02*** 0.02*** 0.02***Somewhatinterested

0.05 0.05 0.05 0.03 0.03 0.03 0.03 0.13*** 0.13*** 0.13*** 0.13***

Very interested 0.32*** 0.32*** 0.33*** 0.24*** 0.24*** 0.24*** 0.25*** 0.37*** 0.37*** 0.38*** 0.38***Left−right scale −0.01 −0.01 −0.01 −0.03** −0.03** −0.03** −0.03**Very proud ofnationality

−0.22*** −0.22*** −0.23*** −0.33*** −0.33*** −0.34*** −0.33*** −0.22*** −0.22*** −0.22*** −0.22***

Income 0.07*** 0.07*** 0.07*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05***Skilled worker 0.06 0.06 0.05 0.06 0.06 0.06 0.07 0.12** 0.12** 0.11** 0.11**Employment status 0.04 0.04 0.04 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.00Constant −0.51* −0.57* −0.68 5.33 0.11 0.08 −5.42 −8.94 (.10) −0.44 −0.33 −0.24 −0.54


0.80*** 0.70*** 0.65*** 0.02*** 0.52*** 0.49*** 0.13*** 0.05*** 0.84*** 0.81*** 0.51*** 0.19***

Stock ofinternationalimmigrants 2008

0.02 0.01 −0.06* −0.03 −0.21**


0.00 0.01 0.01 0.07*

Nationalunemployment2008

0.68** 0.19 0.17 0.35 1.32**

(Continued )

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Table 3. Continued.

DV: ImmigrationInflux Null Individual Contact theory

Economiccompetition Individual Contact theory


Individual(10)

Contacttheory


IV Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff.

Unemploymentrate 2003−2008

−0.88** −0.31 −0.30 −0.45 −1.37**


0.79* 1.23** 0.41 0.72*


0.41 (.10) 0.56** 0.19 0.25*

Gini coefficient,2008

−0.12*** −0.08* −0.11** −0.11* −0.17**

Reliability estimate 1.00 0.99 0.99 0.82 0.99 0.99 0.97 0.93 1.00 1.00 0.99 0.98Log likelihood −10711.9 −4444.59 −4444.33 −4435.26 −6778.86 −6778.60 −6772.97 −6769.37 −9827.69 −9827.46 −9824.52 −9819.24Deviance 21423.84 8889.172 8888.662 8870.522 13557.72 13557.19 13545.93 13538.73 19655.378 19654.928 19649.04 19638.472Number ofobservations

16824 7132 7132 7132 10377 10377 10377 10377 15749 15749 15749 15749

Number ofcountries

10 6 6 6 9 9 9 9 11 11 11 11

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immigrants. At the same time, this finding follows the same pattern as the rest of the lit-erature with a sample of OECD or European countries (e.g. Gang et al., 2002; Mayda,2006; Hainmueller and Hiscox, 2007).

Social capital hypothesis

Either participating in social organization or thinking that others are generally trustworthyis expected to have a positive impact on attitudes toward immigrants and immigration.Even though the results presented here lend further support to the social capital hypothesis,they also suggest that we need to approach the concept of social capital carefully. The twodimensions taken into consideration here propose that involvement in social organizationsand trust in others facilitate cooperation among citizens and lead to a number of positiveoutcomes. However, empirical tests reveal that when put together—that is, each dimensionis controlled for the other—interpersonal trust is the truly positive dimension that is behindthe scenes of social capital and pulls individuals toward more tolerant attitudes vis-à-visimmigrants and a more open migratory policy. Interpersonal trust is, in fact, the only indi-vidual-level variable that is consistently significant for every single model and is unaffectedby the different model specifications. Thus, analyses that only regard the role of involvementin social organizations overlook the powerful effect of interpersonal trust.

Figure 3 displays the magnitude of the effect of interpersonal trust on attitudes towardimmigrants and immigration inflows. A respondent who believes that most of the peoplecan be trusted is expected to hold a positive predisposition toward immigrants with aprobability of 71.9 per cent, while this figure would decrease to 66.1 per cent if the respon-dents feel that most of the people cannot be trusted. The same effect is shown when usingopinion regarding the openness of the migratory policy, as being a social truster boostsrespondents’ attitudes toward more open immigration policy by 8.2 per cent. Again,

Figure 2. Predicted probability of Attitudes towards Immigrants and Immigration Inflow by Edu-cational attainment.


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with varying reliabilities for some coefficients, the direction of the coefficient of truster isconsistent throughout all the models (complete pooling, no pooling, and all models for thethree weighting procedures) for both immigrants and immigration policy.

By contrast, the effect of the second dimension of social capital, involvement in socialorganizations, appears rather contradictory, since it has a positive effect on attitudestoward immigration policy but it does not stem from a more positive view of immigrants.In fact, the positive effect of social organization found in the full model of the sample whencountries are equally weighted is not robust across different specifications and countryweights. The lack of consistency of this coefficient suggests the reader should view the vari-able of social organization with caution.

Political-ideological hypothesis

The interaction between individuals and the political sphere is believed to be anothersource of positive/negative attitudes toward immigrants and immigration accountingfor the relevant literature in Europe and America. Results indicate a certain variabilityin the predictive strength across the three indicators analysed: interest in politics, ideologi-cal orientation and national pride.

Models presented in Tables 2 and 3 reveal that ideological orientation (self-placementon the left–right scale) as well as pride in one’s own nationality consistently predict therelevant attitudes in the expected direction. In this, Figure 4 shows that, all else beingequal, a respondent who is not very proud of their own nationality is more likely toshow a positive attitude toward immigrants of 68.3 per cent, while for the same individualin the same country with the opposite view the probability decreases to 66.5 per cent. Eventhough this change is already statistically significant for people’s attitudes toward immi-grants, the magnitude effect increases substantially when we regard individuals’ opinionstoward immigration inflow policy. Also, if a respondents states they are very proud asopposed to only being quite proud, not very proud or not at all proud, this leads to adecline of 8.1 percentage points in their likelihood to view a more open migratory policypositively. In particular, this means a substantial reduction from 49.3 to 41.2 per cent inthe expected probability to hold a positive orientation toward a more open migratorypolicy. The sign of the effects for all countries in the no-pooling mode, as well as the com-plete pooling, shows a high level of consistency across all countries in the sample.

Figure 3. Predicted probability of Attitudes towards Immigrants and Immigration Inflow by Levels ofSocial Capital.

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Ideological self-placement follows a similar pattern to national pride. It considerablydepresses attitudes toward the phenomenon at both the people and policy levels. Forexample, a respondent with the same personal conditions and country of residencewould reduce their positive view toward immigrants by 12.9 per cent if located in theextreme-right instead of the extreme-left position. This means a very significant fallfrom an expected value of 73.4 to 60.5 per cent acceptance of immigrants. This effecton negative prejudice is partially translated into policy preferences. The same ideologicalshift would mean a change from 44.4 to 38.7 per cent, and so a drop of 5.7 percentagepoints in the expected ideal of openness of the migratory policy. While being proud ofone’s nationality increases people’s negative attitudes toward immigrants and immigrationpolicy in a very consistent manner throughout all the models, the effect of ideology doesnot seem to hold so much consistency. However, the comparability of ideologies acrossnations might undermine these coefficients.

By contrast, interest in politics only becomes significant as a predictor of respondents’opinion on the ideal level of openness of the migratory policy, but not on attitudes towardimmigrants. Those who are very interested in politics have attitudes that do not differ substan-tially from those who are only somewhat or not interested at all in politics. Since the relation-ship between interest in politics and an individual’s level of political information is assumed tobe high, increased political information does not affect people’s opinion on the matter whenthe rest of the potential intervening variables are controlled for, especially education,. However,it does seem to affect people’s preferences regarding migratory policy, since those who aremore interested in politics, and presumably are able to gather more political information,tend to accept higher levels of immigrant flows with a significant increase of 6.1 per cent.

Figure 4. Predicted probability of Attitudes towards Immigrants and Immigration Inflow by PoliticalVariables.


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Contact theory/group threat

Large numbers of immigrants can potentially lead to two diametrically opposed paths. Thecontact between natives and immigrants attenuates intergroup tensions which would leadto a more tolerant view among the former and a better accommodation by the latter in thehost community. By contrast, the negative side of the model suggests that, with a largenumber of immigrants settled in a country, natives feel threatened not only economicallybut also culturally by immigrants. This would lead to higher levels of animadversiontoward them. Nevertheless, the process seems to be even more complex than thought.

Figure 5 demonstrates the relevance of the stock of international immigration in thecountry to understanding people’s attitudes toward immigrants and immigration,although it does so in a complex way. Both sides of the theory seem to be playing a sim-ultaneous but divergent role in the process. Whereas a high number of immigrants in thecountry leads to more contact between natives and immigrants, and increases the favour-able opinion toward immigrants (contact theory), it also leads to a more restrictive policytoward the entry of new immigrants (group threat). Similarly, the recent net migration ratehas the group threat effect on migratory policy although this is not accompanied with theeffect on immigration that the contact theory would expect (predictions of attitudestoward immigrants are not shown in Figure 5 due to an insignificant coefficient).

These results suggest that a positive effect of the number of immigrants in a givencountry on the view of the natives toward immigrants is more likely to be caused by acountry’s history as a receiver of immigrants. This implies that tolerance is not increasedby a short-term increase in immigrants, but, instead, by the stock of international immi-grants—that is, the reception of immigrants over a long period of time.

Economic competition

The agreement shown in the literature on the economic competition hypothesis is basedon the varying perceived threat of immigrants in the competition for scarce resources. Thisimplies different expectations for some individual-level variables. Most obviously, individ-uals with higher income jobs, those who are more skilled and are employed, are expectedto view immigrants as less threatening since they are likely to be more confident in their

Figure 5. Predicted probability of Attitudes towards Immigrants and Immigration Inflow by Immigrantsstock and migration rate.

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chances to successfully compete for jobs with immigrants, and maintain their economicstatus. The opposite is expected to occur among low-skilled workers or the unemployed.Other factors such as the state of the economy, the evolution of national unemploymentare located beyond individual control. These contextual factors were also expected to affectnatives’ perceived economic vulnerability. Overall, results lend credence to the influence ofintergroup competition, although with several exceptions.

As far as the individual-level economic determinants are concerned, Tables 2 and 3, aswell as A1−A4 in the Appendix show the positive effect of respondents’ labour skills on atti-tudes toward immigrants. It shows a consistently significant coefficient across the threedifferent model specifications, and for most of the countries in the region. As expected,those who are high-skilled workers tend to view immigrants more positively as opposedto those with lower-skilled jobs. Even though there is a shift in attitudes, this does not trans-late into a preference towardmore openmigratory policies. By contrast, employment statusseems to be unrelated to people’s perceptions of immigrants, while it does show an impact asregards the preferred openness of the migratory policy. At the same time, relative familyincome appears to be positively related to preference for more open migration policies,although it only provides mixed results in relation to attitudes as it is inconsistently signifi-cant and with a changeable sign in the models toward immigrants.

The country-level economic determinants, national unemployment, national GDP,unemployment rates and national GDP growth in the last five years have only yieldedinconclusive results and their coefficients should be treated with caution in terms of influ-encing attitudes toward immigrants since their impact is rather variable throughout themodels. Yet some of them do show some consistency in terms of migration policy’s pre-ferences. In particular, both GDP per capita and GDP growth in the last five years providesa systematic positive effect on attitudes toward a more open migratory policy. Figure 6shows how an upwards shift of one standard deviation, within the selected countries, inthe GDP per capita or, in other words, an increase from the sample mean of $8,735 to$21,861 leads to an increase in the expected preference over a more open migratorypolicy of 16 per cent, jumping from 32 to 48 per cent. In parallel, the equivalent shiftof one standard deviation in the GDP growth rate means a similar increase of 15 percent, from 32 to 47 per cent, over the acceptance of immigration inflow. By contrast,

Figure 6. Predicted probability of Attitudes towards Immigration inflow by GDP per capita and GDPgrowth.


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national unemployment rate and average annual unemployment rate in the last five yearsdo not follow a very clear pattern in these models either.

Despite the variation in the impact of individual- and contextual-level determinants onattitudes, country inequalities might be regarded as the most regular economic predictor interms of both significance and direction of the effect. As inequalities in a given countryincrease, and so does its Gini coefficient, the less likely it is that an individual from thiscountry will think positively about settled immigrants and the entrance of new immigrants.Comparing the pattern of the two variables, the effect of inequalities on views over immi-grants is smoother and more difficult to achieve, with a lower slope, than it is to changepeople’s opinion over the required openness of the country in relation to new immigrants.Figure 7 clearly shows how the maximum effect on attitudes toward policies is found in achange in the Gini coefficient between 30 and 50. Thus, low inequalities in these countriesnegatively correlates with natives’ resentment with regard to immigrants.

All in all, these findings support the influence of the intergroup competition theory onattitudes toward immigrants and immigration, althoughwith some important reservations.Variables of the economic competition theory provide somemixed results. Only two out ofeight variables linked to this theory yield consistent and significant effects over the favour-able perception of immigrants: respondents’ skill level and theGini coefficient of its countryof residence. By contrast, it seems that intergroup competition theory predicts rather betterpeople’s opinions toward immigration policy. Having a job and living in a developedcountry with a growing economy and low inequalities is positively associated with a prefer-ence for a more open migratory policy quite convincingly throughout the models.

Across different model specifications, all of them to some extent—human capital, socialcapital, political-ideological model, contact theory/group threat and economic compe-tition, and so political as well as economic determinants—do have a role in the processof acceptance or discrimination of immigrants and the ideal openness of the immigrationpolicy in the Asia-Pacific region.

Figure 7. Predicted probability of Attitudes towards Immigrants and Immigration Inflow by CountryInequality.

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Summary of findings

Table 4 summarizes the main findings by showing the correspondence between the direc-tion of the theoretical expectations and the empirical results. Generally speaking, currenttheoretical models perform rather well in the Asia-Pacific region in explaining citizens’perceptions toward immigrant groups and migration policy preferences. However,models fit better for policy orientations (12 out of 16 indicators with significant effectsand the expected direction, or about 75 per cent success rate, although it jumps up to100 per cent if economic determinants are excluded) than for group discrimination (7out of 16 indicators with significant effects, or about 44 per cent success rate). Across the-ories, non-economic theories provide stronger evidence in their support than economictheories (13 out of 15 indicators from non-economic theories) as compared to economiccompetition theories (6 out of 16 indicators).

Discussion and conclusions

The analysis presented in this article provides evidence that current theoretical models, whichhad only been tested in western countries, are largely useful to explain people’s reactionstoward immigrants and their ideal migration policy in countries from Asia and the Pacificregion. Different migration histories and a diverse developmental stage and paths, amongother divergent features, are not obstacles to their extended usefulness. At the same time,some important similarities between these well-studied cases and these results from theAsia-Pacific region should attract the attentionofpolicy-makers.Apolitical strategy is requiredin order to avoid an escalation of social and political tension and the emergence of populist andxenophobic parties as have been witnessed by several European countries in the last decades.

The positive association of human capital is consistent with initial expectations andthus lends credence to the relevance of education to reduce prejudice and negative

Table 4. Summary of results and their consistency with theoretical expectations.

Theories IndicatorsExpectedsign

Most consistent findingsImmigrants(as people)

Immigration(as policy)

Human Capital Educational attainment + + +Social Capital Social trust + + +

Involvement in social organizations + Ø +Political-Ideological Interest in politics + Ø +

Left–right ideological placement − − −National pride − − −

Contact Theory/GroupThreat

Stock of international immigrants, 2008 −/+ + −Migration rate, 2008 −/+ Ø −

Economic Competition Relative income scale + Ø +Skilled worker + + ØEmployment status − Ø +National unemployment rate, 2008 − Ø Ø/+Average annual unemployment rate, 2003–2008

− Ø Ø/+

GDP per capita, log scale, 2008 + Ø +Average annual growth of the GDP per capita,2003–2008

+ Ø +

Gini coefficient, 2008 − − −Ø symbol denotes Coefficients are not consistently different from no-effect.


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attitudes as well as favouring a more liberal migratory policy. For the Asia-Pacificcountries, education remains a significant factor even after adjusting for all the economicpredictors. The effect of education, beyond its economic aspect, supports Hainmueller andHiscox’s (2007) argument regarding the independent effect of the non-labour factors asthe main drivers of the relationship between education and an individual’s open-minded-ness. This strong effect of human capital means that there exists an educational gapbetween those with a high level of education, who hold less discriminatory attitudes,and those with a low level of education, who hold more discriminatory attitudes.

As occurs with human capital, the social capital indicators also yield positive results inreducing tensions between natives and immigrants. However, whereas this is true for theindicator of interpersonal trust for both dependent variables, the effect of involvement insocial organizations only holds up in relation to immigration policy. Thus, policies thatboost a more trusting social view among citizens and encourage participation in socialorganizations would benefit from higher levels of tolerance. Involvement in social life,including intermixed relationships between natives and immigrants—that is, bridgingsocial capital—would foster intergroup cooperation, promote willingness to bridgesocial cleavages and make overtures across group boundaries more feasible (Boix andPosner, 1996; Putnam, 2001). In other words, countries should move from positioningimmigrants in the host society to focusing on the cohesion of societies as a whole by build-ing common areas of understanding among groups.

Additionally, the effect of political-ideological variables is consistent with previousexpectations. On the one hand, interest in politics is assumed to be a function of the indi-vidual’s level of political information and knowledge, and therefore highly sophisticatedcitizens may be more aware of the positive economic consequences of immigration,leading them to be more willing to accept more newcomers. At the same time, it mightalso indicate that immigration constitutes an easy political scapegoat for those with lowlevels of political information. Either reason is only possible as regards immigrationinflow but not for anti-immigrant attitudes, since the effect is generally non-significantfor the latter. This mixed effect casts general doubt about its global plausibility, and soit remains, at least partially, an empirical puzzle.

On the other hand, the importance of the ideological self-placement on the left–rightscale and the respondent’s pride in their own nationality fits with my previous theoreticalexpectations. It also parallels the European reality where tensions between immigrants andhost communities are embedded in ideological and nationalistic battles. When immigra-tion becomes an issue in the political debate, it strains political cleavages, promotes a socialdivide across political lines and, eventually, boosts political radicalization around the issue.Therefore, a reduction in the politicization of migration in the public arena and a generalseeking for political consensus is a crucial element to pacify tensions and maintain lowlevels of anti-immigrant attitudes among natives. Also, the effect of national pride islikely to stem from an ethnic or exclusive understanding of nationhood where foreignersare seen as a danger to the cultural and national hegemony.

Beyond individual-level models, results confirm the need to account and control forcontextual effects. Short- and long-term national characteristics were expected to play asubstantial role in understanding individual attitudes. Empirical results confirm thisexpectation. The contact theory is supported by the positive relationship between thenumber of immigrants in a country and the tendency of their inhabitants to view

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immigrants more favourably. In parallel, the group threat theory plays its role in increas-ing unfavourable views toward immigration policy. Here, the findings allow me to dis-tinguish a dual process that takes place in the sample of countries under study.Evidence suggests that a more gradual influx of immigrants, that is, with sufficient timefor their accommodation to the new society, would assuage intergroup tensions giventhat recent net migration rates lead to preferences for more restrictive policies. Finally,it is not clear from the data explored here that discrimination is linked to economic com-petition. Of the eight variables in the economic competition theory, only two of them(skilled worker and inequality coefficient) provide significant results.

All in all, empirical findings point to several promising lines of research. For instance,even though current theoretical models are able to capture a great deal of within- andcross-country variation, identification of additional general causes as well as country-specific determinants should inform future inquiries. Moreover, the striking divergencebetween attitudes toward immigrants and opinions regarding immigration policy castsdoubt over their assumed common source. This should definitely warn scholars aboutthe need to find out the underlying micro-mechanisms.

However, the results shown here should be treated with some caution since they rely fordata on only two questions from the World Values Survey (2005–2008) and for amaximum of 11 countries, which, although chosen as representatives of the region, canhardly capture the full variation for a region as diverse as the Asia-Pacific. This is especiallytrue for the contextual-level variables where the limitations in terms of degree of freedomdue to the small-N at the group level has impeded maximizing the efficiency of the modelsand incorporating second-level controls in conjunction with the main contextual indepen-dent variables. Additionally, it could be argued that attitudes toward immigrants andimmigration inflow are shaped by previous country-specific policies aimed toward immi-grants directly (policies directed to improve the image of immigrants, for instance) andbeyond the indirect effects of the stock of international immigrants and the migrationrate (by-products of immigration policies).

In addition to this, there are some measurement issues that should be improved infuture work. To start with, the validity of measurement based on a cross-nationalsurvey constitute a common limitation for all research that works with cross-national vari-ation of social and political attitudes (Davidov et al., 2014). In addition to this, it is some-times difficult to test the validity of the measures—that is, the extent to which the measurestap into the theoretical concept as they are intended to. This is a limitation of this papershared with most research into contextual effects on attitudes toward immigrants. Thus,improving our measures of the economic competition theory of the contact/groupthreat theory would certainly improve our model. Furthermore, current research islimited to the data available. Thus, the lack of data capturing the depth and breadth ofthe migration policies in each country is a limitation of this research that is also sharedwith most in the American or European context. Nevertheless, the potential of theresults should encourage more efforts on this line and the development of plans tonourish the region with more high-quality survey data. Moreover, macro-observationaldata has empirical limitations for causal inference that might be overcome in the futureby micro-level research and experimental data.

In any case, the increase in the number of international migrants in the Asia-Pacificpushes policy-makers to focus their attention on reaping the benefits and controlling


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the negative potential consequences of immigration. Knowing what affects discriminationand animadversion toward immigrants is crucial to ensure social well-being, as it willallow policy-makers to remove its causes, assuage intergroup tensions, and maintainsocial harmony in the long term.

Notes

1. My definition of immigrant is given by my data. Therefore, I define ‘immigrants’ as thoseincluded as part of the international migration stock provided by the UN Population Division.The UN estimates the number of international immigrants depending on the availability of datafor each country and may refer to the foreign-born population or to foreign citizens; it mightinclude the number of refugees as international immigrants and, in some cases, the figure hasbeen obtained by imputation. For more information about the source of the specific estimates,see the UN Population Division (2013).

2. The complete list of groups included in the original wording of the question is the following:drug addicts, people of a different race, people who have AIDS, immigrants/foreign workers,homosexuals, people of a different religion, heavy drinkers, unmarried couples living together,people who speak a different language, militant minority, people with a criminal record.

3. This variable captures the likelihood of an individual facing competition for jobs in the marketagainst immigrants in actual or potential terms. For instance, even if a farmer is self-employedand is not likely to compete against immigrants for jobs, the farmer might face potential highereconomic competition since, in case of unemployment, his or her chances of finding a job areaffected by the number of immigrants in the country. Thus worker’s skills are a good proxy offuture employability and wage change in the face of immigration.

4. Discrepancies between attitudes toward immigrants and immigration inflow or policy areexpected to emerge, as can be seen from Figure 1, when the determinants that affect one andthe other differ and have different intensity. In this regard, even though the theoretical frame-work for both dimensions is the same, the empirical results might well explain within-countrydiscrepancies between orientation toward immigrants as a group and immigration as aphenomenon.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributor

Joan Barceló is currently a Ph.D. student in the Department of Political Science at WashingtonUniversity in St. Louis. Also, he has been a researcher at the University of Barcelona, UniversitatPompeu Fabra, New York University, and UN-ESCAP in Bangkok.

Acknowledgements

I am grateful for the comments of Lucia González, Maren Andrea Jiménez, Srinivas Tatas andVanessa Steinmayer on aspects of the paper; to the La Caixa Fellowship Programme and theSocial Development Division at the United Nations – Economic and Social Commission for Asiaand the Pacific for their support during my research; all errors remain my own.

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Appendix

Table A1. Determinants of positive attitudes toward immigrants (observations unweighted).



Contacttheory


Contacttheory



Sex −0.03 −0.04 −0.03 −0.03 −0.01 −0.01 −0.01 0.00 0.01 0.01 0.01 0.01Age −0.09* 0.02* 0.02* 0.02* 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.00Age square 0.04* 0.00* 0.00* 0.00* 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Size town 0.02*** 0.05*** 0.06*** 0.06***Immigrant 0.00 0.21 (.19) 0.14 0.14Education secondary −0.01 −0.07 −0.05 −0.06 0.12* 0.11 (.10) 0.11 (.12) 0.11 (.10) 0.13** 0.13** 0.13** 0.13**Education university 0.05 0.05 0.08 0.07 0.25*** 0.23*** 0.23*** 0.20*** 0.21*** 0.21*** 0.21*** 0.21***Truster 0.19*** 0.32*** 0.31*** 0.31*** 0.34*** 0.34*** 0.34*** 0.36*** 0.26*** 0.26*** 0.26*** 0.26***Social organization −0.03*** −0.03*** −0.03*** −0.03*** −0.02*** −0.02*** −0.02*** −0.02*** −0.01*** −0.01*** −0.01** −0.01***Somewhat interested −0.16 −0.10

(.12)−0.09 (.15) −0.09

(.16)−0.07 −0.08 (.17) −0.07 −0.06 0.02 0.02 0.02 0.02

Very interested 0.09 (.11) −0.13* −0.14* −0.14* −0.08 −0.08 −0.08 −0.05 −0.07 −0.07 −0.07 −0.07Left−right scale −0.13** −0.03** −0.03** −0.03** −0.07*** −0.06*** −0.07*** −0.06***Very proud ofnationality

−0.08** −0.17*** −0.18*** −0.18*** −0.13** −0.12** −0.12* −0.09(.12)

−0.13*** −0.13*** −0.13*** −0.13***

Income 0.31 −0.02 −0.02 −0.02 0.02 (.18) 0.02 (.20) 0.02 (.17) 0.03* 0.01 0.01 0.01 0.01Skilled worker −0.03

(.14)0.08 0.09 .(16) 0.09 (.15) 0.15*** 0.16*** 0.16*** 0.18*** 0.14*** 0.14*** 0.14*** 0.14***

Employment status −0.02 −0.04 0.01 0.00 −0.03 −0.04 −0.03 −0.02 −0.08 −0.08 −0.07 −0.07Constant 0.82*** 0.87* 0.35 −8.10** 4.11* 0.92** 0.51* 15.25 1.38** 0.78** 0.45 (.15) −2.18 −0.65


0.59*** 0.57*** 0.00*** 0.00 .19 0.00 0.48*** 0.03*** 0.12*** 0.00* 0.55*** 0.32*** 0.25*** 0.19***


0.11*** 0.15** 0.11*** 0.08** 0.08* 0.07 (.11)


−0.01* − −0.01 (.13) 0.01 0.00


− − 0.89 (.18) 0.15 (.15) 0.09

(Continued )

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Table A1. Continued.



Contacttheory


Contacttheory




− − −0.09 (.18) −0.11 −0.08


1.06*** −0.48* −0.06 − 0.55* 0.23


0.24** − −0.68 − 0.18 (.17) 0.18 (.10)

Gini coefficient, 2008 −0.04** 0.01 −0.12* −0.03** −0.08* −0.05(.13)

Reliability estimate 0.99 0.99 0.53 0.00 0.00 0.99 0.83 0.96 0.00 0.99 0.99 0.98 0.97Log likelihood −9661 −4269.5 −9909.5 −4259.79 −4259.1 −5874.59 −5866.43 −5868.63 13340.12 −9115.27 −9114.05 −9111.58 −9111.68Deviance 19322.5 8539.0 19819.0 8519.6 8518.3 11749.18 11732.86 11737.25 −26680.2 18230.53 18228.10 18223.15 18223.35Number ofobservations

15433 7005 7005 7005 7005 9441 9441 9441 9441 14526 14526 14526 14526


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Table A2. Determinants of positive attitudes toward immigrants (observations weighted by population size of country of belonging).



Contacttheory


Contacttheory



Sex 0.05 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.01 0.01 0.01 0.01Age 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 −0.02

(.11)−0.02 (.11) −0.02 (.11) −0.02

Age square 0.00 (.16) 0.00 (.16) 0.00 (.16) 0.00 0.00 (.20) 0.00 0.00 (.20) 0.00 0.00 0.00 0.00 0.00Size town 0.08*** 0.07*** 0.08*** 0.08***Immigrant −0.02 −0.02 −0.03 −0.03Education secondary 0.03 0.02 0.03 0.03 0.12 0.12 0.11 0.12 0.07 0.07 0.06 0.07Education university 0.15 0.15 0.15 0.15 0.23* 0.22* 0.22 (.10) 0.22* 0.08 0.08 0.08 0.08Truster 0.66*** 0.66*** 0.67*** 0.66*** 0.63*** 0.63*** 0.63*** 0.63*** 0.27*** 0.27*** 0.27*** 0.27***Social organization −0.02* −0.02* −0.02** −0.02** −0.02** −0.02** −0.02* −0.02** −0.02** −0.02** −0.02*** −0.02**Somewhat interested −0.04 −0.04 −0.04 −0.04 −0.05 −0.06 −0.05 −0.06 −0.05 −0.05 −0.05 −0.05Very interested 0.02 0.02 0.02 0.02 0.03 0.02 0.04 0.02 −0.12

0.18−0.13 (.18) −0.13 (.17) −0.13

(.17)Left−right scale −0.02 −0.02

(.17)−0.02 −0.02

(.19)−0.03** −0.03** −0.04** −0.03**

Very proud ofnationality

0.05 0.05 0.05 0.05 0.05 0.05 0.06 0.05 0.06 0.06 0.07 0.07

Income −0.07*** −0.08*** −0.07*** −0.07*** −0.05** −0.05** −0.05** −0.04** −0.020.14

−0.02 (.14) −0.02 0.14 −0.02(.14)

Skilled worker 0.08 (.14) 0.08 0.08 0.08 0.13 (.20) 0.14 (.16) 0.14 (.17) 0.14 (.15) 0.22*** 0.22*** 0.22*** 0.21***Employment status −0.21 −0.22 −0.21 −0.21 −0.19 −0.19 −0.18 −0.19 0.00 0.00 0.00 0.00Constant 0.92*** 0.22 0.11 −7.14** 1.35 0.35 0.23 5.15 0.72 1.33*** 1.41*** −3.13* −1.96


0.20*** 0.06*** 0.00 0.00 0.00 0.07*** 0.00** 0.02*** 0.00** 0.16*** 0.15*** 0.03*** 0.02***


0.12*** 0.11 (.13) 0.15*** 0.13*** −0.04


−0.01(.10)

−0.02*** −0.01* 0.03 0.19 0.03**


− 0.35 −0.21 (.18) −0.08

(Continued )

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Table A2. Continued.



Contacttheory


Contacttheory




− −0.35 0.22 (.19) 0.13


0.96** −0.12 −0.06 0.50*** 0.29*


0.16 −0.24 0.21*** 0.21***

Gini coefficient, 2008 −0.04** −0.01 −0.06 0.12 −0.01−0.04** −0.03*


15433 7005 7005 7005 7005 9441 9441 9441 9441 14526 14526 14526 14526


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Table A3. Determinants of positive attitudes towards immigration policy (observations unweighted).

DV: Immigration Inflow Null IndividualContacttheory

Economiccompetition Individual

Contacttheory


Contacttheory


IV Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff.Sex −0.01 −0.01 −0.01 −0.04 −0.04 −0.04 −0.04 −0.08** −0.08** −0.08** −0.08*Age −0.01 −0.01 −0.01 −0.01 −0.01 −0.01 −0.01 −0.02** −0.02** −0.02** −0.02**Age square 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Size town 0.01 0.01 0.02Immigrant −0.05 −0.06 −0.06Education secondary 0.06 0.06 0.06 0.07 0.07 0.07 0.07 0.21*** 0.21*** 0.20*** 0.21***Education university 0.15 (.11) 0.15 (.11) 0.14 (.13) 0.17** 0.17** 0.16** 0.16** 0.30*** 0.30*** 0.30*** 0.31***Truster 0.32*** 0.32*** 0.32*** 0.34*** 0.34*** 0.34*** 0.34*** 0.35*** 0.35*** 0.35*** 0.35***Social organization 0.00 0.00 −0.01 0.00 0.00 0.00 0.00 0.02*** 0.02*** 0.02*** 0.02***Somewhat interested 0.08 0.08 (.19) 0.07 0.05 0.05 0.05 0.05 0.16*** 0.16*** 0.16*** 0.16***Very interested 0.35*** 0.35*** 0.35*** 0.28*** 0.28*** 0.28*** 0.28*** 0.42*** 0.42*** 0.42*** 0.42***Left−right scale −0.02

(.18)−0.02 (.19) −0.01 −0.03*** −0.03*** −0.03*** −0.03**

Very proud of nationality −0.20*** −0.20*** −0.20*** −0.31*** −0.31*** −0.31*** −0.30*** −0.18*** −0.18*** −0.18*** −0.18***Income 0.07*** 0.07*** 0.07*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05***Skilled worker 0.05 0.05 0.04 0.05 0.05 0.04 0.05 0.10** 0.10** 0.10** 0.10**Employment status 0.06 0.06 0.06 0.04 0.04 0.04 0.04 0.01 0.01 0.01 0.01Constant −0.52* −0.63

(.19)−0.73 5.26** −0.05 −0.08 −5.55 −9.16

(.10)−0.55(.11)

−0.47 −1.35 −1.29

Random-effects parametersIntergroup variancecomponent

0.75*** 0.70*** 0.64*** 0.02*** 0.56*** 0.53*** 0.13*** 0.06*** 0.80*** 0.78*** 0.45*** 0.18***


0.02 0.01 −0.06* −0.02 −0.20**

Net migration rate 2003−2008

0.00 0.01 0.01 0.06*

National unemployment2008

0.65** 0.19 0.17 0.34 1.21**

Unemployment rate 2003−2008

−0.84** −0.32 −0.30 −0.44 −1.25**

GDP per capita, log scale2008

0.79* 1.24** 0.48 0.74*

Growth of GDPpc, 2003–2008 0.41 (.10) 0.55** 0.21 (.16) 0.24*Gini coefficient, 2008 −0.12** −0.08* −0.10** −0.10* −0.16*

Reliability estimate 1.00 0.99 0.99 0.82 0.99 0.99 0.97 0.93 1.00 1.00 0.99 0.98Log likelihood −10718.27 −4435.11 −4434.84 −4425.82 −6720.05 −6719.76 −6713.86 −6710.62 −9832.64 −9832.43 −9829.04 −9824.20Deviance 21436.54 8870.23 8869.69 8851.65 13440.09 13439.52 13427.72 13421.23 19665.28 19664.86 19658.09 19648.40Number of observations 16824 7132 7132 7132 10377 10377 10377 10377 15749 15749 15749 15749Number of countries 11 6 6 6 9 9 9 9 11 11 11 11

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Table A4. Determinants of positive attitudes toward immigration policy (observations weighted by population size of country of belonging).

DV: ImmigrationInflow Null Individual

Contacttheory


Contacttheory


Contacttheory


IV Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff. Coeff.Sex −0.02 −0.02 −0.02 −0.02 −0.04 −0.04 −0.04 −0.04 −0.15** −0.15** −0.15** −0.15**Age 0.01 0.01 0.01 0.01 0.00 0.00 0.00 0.00 −0.01 (.19) −0.01 (.19) −0.01 (.19) −0.02 (.19)Age square 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00Size town 0.01 0.01 0.01 0.01Immigrant −0.48** −0.48** −0.49** −0.49**Education secondary 0.27** 0.27** 0.27** 0.28** 0.23** 0.23** 0.24** 0.24** 0.34*** 0.34*** 0.34*** 0.35***Education university 0.22 (.15) 0.22 (.15) 0.22 (.15) 0.22 (.15) 0.19 (.14) 0.19 (.14) 0.19 (.14) 0.19 (.14) 0.36*** 0.36*** 0.36*** 0.36***Truster 0.44*** 0.44*** 0.44*** 0.45*** 0.42*** 0.42*** 0.42*** 0.42*** 0.35*** 0.35*** 0.35*** 0.35***Social organization 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.03*** 0.03*** 0.03*** 0.03***Somewhatinterested

0.26** 0.26** 0.27** 0.27** 0.19** 0.19** 0.19** 0.19** 0.34*** 0.34*** 0.34*** 0.34***

Very interested 0.61*** 0.61*** 0.61*** 0.61*** 0.48*** 0.48*** 0.48*** 0.48*** 0.60*** 0.60*** 0.60*** 0.60***Left−right scale −0.08*** −0.08*** −0.07*** −0.07*** −0.06*** −0.06*** −0.06*** −0.06***Very proud ofnationality

−0.07 −0.07 −0.04 −0.07 −0.11 −0.11 −0.11 −0.11 0.07 0.07 0.07 0.07

Income 0.08*** 0.08*** −0.07*** 0.08*** 0.07*** 0.07*** 0.07*** 0.07*** 0.07*** 0.07*** 0.07*** 0.08***Skilled worker −0.06 −0.06 −0.06 −0.06 −0.06 −0.06 −0.06 −0.06 0.05 0.05 0.04 0.04Employment status 0.42** 0.42** 0.42** 0.42** 0.40** 0.40** 0.40** 0.40 −0.02 −0.02 −0.02 −0.02Constant −0.38 −0.89 −0.99

(.19)−13.25 (.12) 15.30* −0.58 −0.70 −5.05 −7.64

(.16)−0.62 −0.50*** −6.83** −7.18*


0.29*** 0.36*** 0.33*** 0.11*** 0.05*** 0.32*** 0.30*** 0.06*** 0.06*** 0.43*** 0.41*** 0.10*** 0.07***

Stock ofinternationalimmigrants 2008

0.07 0.26** 0.08 −0.04(.18)

−0.11 −0.17**


−0.02 −0.03 0.04 0.04 (.11)

Nationalunemployment2008

−0.16* 0.59* 0.46 (.18) 0.55* 0.70*

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−0.66* −0.53(.15)

−0.59* −0.71*


1.11 (.11) −1.96** 0.73* 0.99* 0.88*** 1.06**


0.66 (.11) 0.27 (.13) 0.36 (.13) 0.27*** 0.30**

Gini coefficient,2008

−0.04 −0.08** −0.08* −0.08** −0.11**


16824 7132 7132 7132 7132 10377 10377 10377 10377 15749 15749 15749 15749

Number of countries 11 6 6 6 9 9 9 9 11 11 11 11

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Table A5. No-pooling and complete pooling models for immigration policy.Dependent variable:

Support for liberal immigration policy

Japan Australia Korea India China Turkey Georgia Thailand Indonesia Vietnam Malaysia All

Sex 0.044 0.194 0.076 0.002 −0.329*** −0.402*** 0.139 −0.207 −0.165 −0.029 −0.087 −0.045(0.156) (0.128) (0.127) (0.150) (0.111) (0.140) (0.154) (0.149) (0.146) (0.127) (0.204) (0.034)

Age −0.047 −0.020 −0.124*** 0.0002 −0.046* 0.042* −0.072*** 0.058** 0.035 0.043** −0.0004 0.012**(0.031) (0.021) (0.031) (0.025) (0.027) (0.024) (0.026) (0.027) (0.033) (0.020) (0.052) (0.006)

Age sq 0.0003 0.0001 0.001*** −0.00003 0.0002 −0.0004 0.001*** −0.001** −0.0005 −0.001** 0.0001 −0.0002**(0.0003) (0.0002) (0.0003) (0.0003) (0.0003) (0.0003) (0.0003) (0.0003) (0.0004) (0.0002) (0.001) (0.0001)

Size town 0.044* 0.046 −0.009 0.302*** −0.081*** 0.164*** 0.054(0.027) (0.045) (0.028) (0.049) (0.028) (0.060) (0.043)

Immigrant 0.261 13.550 −0.593*** −0.068 −0.110 0.217 −13.302 −0.438 −0.040 0.457***(0.165) (378.559) (0.222) (0.348) (0.894) (1.187) (504.155) (0.375) (0.641) (0.092)

Secondary education −0.032 −0.814*** 0.344 0.371** 0.419*** 0.164 −0.623 0.376* 0.155 −0.385** 0.415 0.253***(0.307) (0.303) (0.257) (0.175) (0.126) (0.157) (0.656) (0.194) (0.218) (0.158) (0.352) (0.043)

University education 0.173 −0.351 0.437 0.312 1.034*** −0.119 −0.680 −0.010 0.045 0.105 0.690 0.508***(0.338) (0.313) (0.281) (0.199) (0.274) (0.248) (0.672) (0.260) (0.249) (0.293) (0.420) (0.052)

Some interest in politics −0.147 −0.056 −0.045 0.350** 0.361*** 0.001 0.409** −1.102*** 0.216 0.346** 0.228 0.187***(0.172) (0.138) (0.135) (0.150) (0.130) (0.138) (0.168) (0.184) (0.156) (0.156) (0.221) (0.037)

Very interested in politics −0.131 0.387* 0.065 0.674*** 0.601*** 0.102 0.202 −0.958*** 0.647*** 0.498*** 0.578 0.691***(0.252) (0.205) (0.319) (0.194) (0.139) (0.226) (0.233) (0.236) (0.239) (0.169) (0.456) (0.050)

Income 0.014 0.015 0.045 0.081** 0.109*** 0.021 0.038 0.252*** 0.001 0.055 0.049 0.018**(0.028) (0.025) (0.037) (0.035) (0.030) (0.032) (0.045) (0.046) (0.036) (0.042) (0.059) (0.008)

Proud nationality −0.315 −0.421*** −0.031 −0.072 0.189 −1.039*** 0.136 −0.755*** −0.043 −0.084 −0.320 −0.306***(0.194) (0.140) (0.165) (0.157) (0.131) (0.157) (0.188) (0.191) (0.140) (0.167) (0.215) (0.034)

Truster 0.102 0.821*** 0.631*** 0.605*** 0.247** 0.112 0.424** 0.239 −0.042 0.133 1.097*** 0.481***(0.155) (0.129) (0.143) (0.158) (0.108) (0.288) (0.185) (0.153) (0.144) (0.123) (0.267) (0.036)

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Participation in socialorganizations

0.060* 0.066*** 0.066** 0.015 0.010 −0.055 0.068 −0.082*** −0.050** 0.030 0.008 −0.009**

(0.034) (0.024) (0.027) (0.014) (0.022) (0.052) (0.081) (0.020) (0.021) (0.023) (0.027) (0.004)

Left–right scale 0.007 −0.082** −0.032 −0.095*** −0.070*** −0.025 0.137*** 0.023 0.044(0.042) (0.034) (0.032) (0.024) (0.025) (0.035) (0.048) (0.031) (0.043)

Skilled worker 0.086 0.194 −0.154 −0.069 −0.107 0.023 0.349** −0.165 0.0004 0.172 −0.134***(0.173) (0.167) (0.160) (0.143) (0.157) (0.171) (0.164) (0.160) (0.149) (0.235) (0.037)

Constant 1.018 0.919 2.621*** −0.712 0.839 0.382 0.846 −3.503*** −1.415** −0.806 −3.266*** −0.975***(0.782) (0.601) (0.676) (0.601) (0.616) (0.521) (0.881) (0.739) (0.673) (0.598) (0.953) (0.135)

Observations 790 1,200 1,196 979 1,576 1,129 860 1,383 1,318 1,392 1,193 15,749Log likelihood −521.688 −744.430 −753.256 −639.397 −1,002.140 −740.079 −507.550 −597.002 −659.444 −814.030 −362.788 −10,247.490Akaike Inf. Crit. 1,071.376 1,520.860 1,534.512 1,310.794 2,030.281 1,510.157 1,047.099 1,226.003 1,350.889 1,660.060 755.576 20,522.980

*p < 0.1; **p < 0.05; ***p < 0.01

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Table A6. No-pooling and complete pooling models for immigrants (as people).

Dependent variable

Attitudes toward immigrants

Australia Korea India China Turkey Georgia Thailand Indonesia Vietnam Malaysia AllSex −0.197 0.263** 0.136 −0.227* −0.216 0.321* −0.118 −0.024 −0.217* −0.079 0.065*

(0.285) (0.127) (0.153) (0.134) (0.156) (0.171) (0.114) (0.126) (0.120) (0.124) (0.037)

Age 0.063 −0.075** 0.019 −0.028 0.038 −0.053* 0.002 0.015 0.027 −0.024 0.007(0.042) (0.030) (0.025) (0.033) (0.027) (0.031) (0.021) (0.027) (0.020) (0.031) (0.006)

Age sq −0.001 0.001** −0.0003 0.0002 −0.0004 0.001 −0.0001 −0.0001 −0.0002 0.0003 −0.00001(0.0004) (0.0003) (0.0003) (0.0004) (0.0003) (0.0003) (0.0002) (0.0003) (0.0002) (0.0004) (0.0001)

Size town −0.052 0.134*** 0.133*** −0.059 −0.007 0.202*** 0.097***(0.062) (0.048) (0.032) (0.042) (0.026) (0.057) (0.026)

Immigrant 0.193 −13.195 −0.079 0.339 −1.294 −0.882 −1.350 1.645*** 0.426(0.383) (378.521) (0.224) (0.426) (0.895) (0.973) (1.234) (0.549) (0.391)

Secondary education 0.548 0.459* 0.014 0.469*** 0.543*** 0.326 −0.224 0.357* −0.164 0.540*** 0.171***(0.469) (0.259) (0.180) (0.155) (0.175) (0.688) (0.157) (0.187) (0.148) (0.194) (0.045)

University education 0.916* 0.843*** 0.179 0.405 0.429 0.521 −0.365* 0.274 0.164 0.137 0.475***(0.521) (0.283) (0.205) (0.350) (0.307) (0.710) (0.211) (0.212) (0.260) (0.254) (0.056)

Some interest in politics −0.142 −0.217 −0.034 −0.073 −0.143 −0.078 −0.233 −0.148 −0.020 0.758*** 0.034(0.308) (0.134) (0.153) (0.157) (0.156) (0.185) (0.158) (0.136) (0.154) (0.136) (0.040)

Very interested in politics −0.082 0.348 0.044 −0.218 −0.188 −0.102 −0.161 −0.336 −0.360** 0.801** 0.018(0.458) (0.336) (0.203) (0.162) (0.255) (0.251) (0.194) (0.225) (0.162) (0.323) (0.055)

Income 0.027 −0.057 −0.122*** 0.033 0.119*** −0.066 −0.042 0.042 0.057 −0.002 −0.056***(0.056) (0.038) (0.036) (0.036) (0.039) (0.050) (0.032) (0.032) (0.040) (0.036) (0.009)

Proud of nationality −0.337 0.088 0.133 −0.114 −0.442** 0.011 −0.637*** −0.045 −0.570*** −0.391*** −0.190***(0.328) (0.167) (0.157) (0.155) (0.184) (0.204) (0.175) (0.122) (0.168) (0.135) (0.038)

Truster 1.307*** 0.390*** 1.064*** 0.147 −0.120 −0.061 0.144 0.043 0.073 0.264 0.353***(0.350) (0.140) (0.178) (0.129) (0.322) (0.209) (0.118) (0.125) (0.115) (0.215) (0.040)

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Participation in social organizations 0.012 0.028 −0.021 0.087*** 0.049 −0.039 −0.050*** 0.058*** −0.065*** 0.030* −0.021***(0.054) (0.026) (0.014) (0.033) (0.073) (0.089) (0.014) (0.018) (0.020) (0.018) (0.004)

Left–right scale −0.079 −0.081** −0.022 −0.137*** −0.11*** −0.112*** 0.008 0.175***(0.072) (0.033) (0.024) (0.029) (0.039) (0.034) (0.027) (0.042)

Skilled worker 0.356 0.157 0.254 0.341* 0.178 0.249* −0.059 −0.094 −0.198 0.302***(0.325) (0.164) (0.186) (0.180) (0.186) (0.131) (0.139) (0.140) (0.141) (0.041)

Constant 0.891 1.683** 0.098 1.824** 0.757 2.194** 2.130*** −0.234 −1.387** −0.618 0.405***(1.171) (0.654) (0.613) (0.774) (0.578) (0.973) (0.586) (0.564) (0.578) (0.555) (0.143)

Observations 1,132 1,181 972 1,551 1,129 845 1,374 1,290 1,392 1,190 14,526Log likelihood −209.96 −754.560 −615.732 −766.497 −616.059 −436.52 −898.353 −809.245 −881.822 −773.199 −8,991.750Akaike Inf. Crit. 451.917 1,537.120 1,263.464 1,558.994 1,262.118 905.049 1,828.706 1,650.490 1,795.644 1,576.398 18,009.500

*p < 0.1; **p < 0.05; ***p < 0.01

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