Socioeconomic Status And Attitudes Towards Immigration In The Republic Of Ireland

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Socioeconomic status and attitudes towards immigration in the Republic of Ireland

Andrew Grier

Department of Sociology, Demography Unit (SUDA) Master’s Thesis 15 HE credits

Subject: Demography

Master’s Programme in Demography (60 credits) Spring term 2021

Supervisor: Caroline Uggla

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Abstract

Attitudes towards immigration in Ireland are the focus of this study and, more specifically, what aspects of life the native-born population perceive to be impacted by immigration into Ireland in 2018. This thesis uses two primary socioeconomic attributes of the native-born respondents as explanatory variables, focusing on education and income levels of the native-born population. The aim of this study is to examine the association between attitudes towards immigration, across different attitudinal dimensions, and socioeconomic status of native-born individuals in the Republic of Ireland in 2018.

This thesis uses data taken from round 9 of the European Social Survey and purports that individuals (i) without tertiary education and (ii) on low-incomes will be more likely to oppose immigration across all dimensions of attitudes to immigration, all else equal. In addition, it propagates the idea that individuals will be more likely to oppose immigration due to the perceived effect of immigration on the economy, all else being equal.

This research draws on Group threat theory and Contact theory as the foundation for the hypotheses and research questions and enables investigation into the primary socioeconomic determinants influencing attitudes towards immigration in Ireland. Furthermore, whether an association exists between socioeconomic status and attitudes across all attitudinal dimensions is explored.

The results indicate that, all else equal, those who studied to at least a tertiary level are more likely to display positive attitudes towards immigration than those without a tertiary education, regardless of attitudinal dimension. Similarly, those on the highest incomes are more likely to exhibit positive attitudes to immigration across all dimensions compared to their low-income counterparts, all else being equal. Interestingly however, this thesis did not find statistically significant evidence that individuals will be more likely to oppose immigration due to the perceived impact of immigration on the economy, as was originally hypothesised.

Keywords: Immigration, Attitudes, Republic of Ireland, Socioeconomic Status, Attitudinal Dimensions

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Attitudes towards immigration are shaped by various factors on both an individual and group level worldwide. Scholars have proposed that socioeconomic attributes of the native-born population play their part in shaping these attitudes (Garcia-Faroldi, 2017; Manstead, 2018; van Heerden et al., 2017).

This thesis intends to investigate how these specific factors are associated with attitudes towards in- migration into the country of study for this thesis - The Republic of Ireland. The thesis will attempt to answer this question by measuring across three distinct attitudinal dimensions and determining how educational attainment and income level, the two primary socioeconomic determinants, are associated with positive or negative attitudes towards immigration. This will be studied against the backdrop of dynamically shifting attitudes towards immigration in recent times, with a specific focus on the Republic of Ireland as a case study. Its unique position within Europe, with one of the highest immigration rates per 1,000 inhabitants across the continent, according to European Union Statistics on international migration flows makes it an interesting choice (Eurostat, Migration, and migrant population statistics, 2020).

In 2018, the Republic of Ireland experienced a net inward migration surplus of 34,000 people (Central Statistics Office Ireland (CSO), 2019). This represents the highest level of net inward migration since 2009 and, similarly, the largest number of immigrants arriving on the island of Ireland since the turn of the 21^st century. The incoming migrants are of diverse nationalities, ages, and religions, arriving on the island with the intentions of living and working in one of the strongest and flourishing economies in the European Union (CSO Ireland, 2019). As of April 2018, there were 593,600 non-Irish nationals’

resident in Ireland, which accounts for 12.2% of the entire population (CSO Ireland, 2019).

Given recent shifts in migration flows over the past two decades Ireland has come to be regarded as an immigrant nation rather than being “characterised as an emigrant country” as it was previously for the better part of the last century (Turner et al., pp. 372: 2015). This is a relatively recent phenomenon given the historically emigrant nature of the island pre the year 2000 and as such attitudes towards immigration are somewhat difficult to predict. In a European context, Garcia-Faroldi in her 2017 paper

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discusses how, since 2008, Eurobarometers developed by various EU institutions state that the percentage of people who are of the belief that their country has not benefitted from being an EU member has increased” (Garcia-Faroldi, pp. 10: 2017), eroding the image of the EU in the process.

This Eurosceptic view has spread throughout Europe in recent times, manifested often by extreme right- wing parties’ popularity (Bridges et al., pp. 413: 2014). Although Ireland’s political leanings remained relatively unaltered in that period, the general shift towards increasingly negative attitudes towards immigration has not evaded a country considered to be liberal in a comparative European context in this regard, as is the case with Ireland. For this reason, within a European context, I have chosen to study Irish viewpoints solely, to assess the current state of attitudes towards immigration. The year 2018, and specifically round 9 of the ESS, was selected as the year of study. This is due to the fact that the impact of economic despair on attitudes towards immigration has already been widely studied and so I am striving to test an alternative aspect, as such intentionally avoiding the crisis years of 2008 to 2015 as a consequence.

In reference to Irish immigration, one conference paper published in 2019 stated that “since the onset of the economic crisis, public opinion in many European countries has become more hostile towards migration, particularly in those countries most affected by economic recession” (American Sociological Association (ASA), pp. 2: 2019). Ireland was one of the worst affected countries in Europe by the global downturn, with ‘significant and rapid immigration and a deep recession’ (ASA, 2019) and yet has recovered, both in terms of economic prosperity and increased migration rates (CSO Ireland, 2019).

Keeping this in mind, this thesis will focus on the attitudes towards immigration in the Republic of Ireland in 2018 and how these attitudes are associated with the socioeconomic status of native-born citizens, across different attitudinal dimensions. The impact of socioeconomic status on attitudes and how the respondents perceive immigration to affect the economy and cultural life will be examined, alongside examining two socioeconomic determinants which influence these attitudes. The backdrop of a return to economic stability provides an interesting foundation for the discussion as regards the different attitudinal dimensions being tested here.

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3 Current Migration to Ireland

Since 2014 Ireland has once more returned to its characterisation as a country with net inward migration, having recovered from the financial crisis of 2008 sufficiently (Department of Justice for Ireland, 2020).

According to the OECD’s data for the percentage of the population who is foreign born, Ireland ranked 7^th worldwide in terms of the highest number of people resident in the country who still hold the nationality of their home country according to statistics released for 2019. As of statistics released midway through 2018 by the same organisation, the largest grouping from one single nation remains people from the United Kingdom (110,000) due to the historical and cultural ties between the two nations. The next largest group consists of those from EU countries who joined in the latest rounds of EU enlargement. The total number of immigrants from those nations stands at 255,000, with the breakdown to the nearest thousand as follows: Poland (122,000), Lithuania (37,000), Romania (29,000), Latvia (20,000), Slovakia (10,000). The remaining countries in this grouping are less than 10,000 in total per country and so are not included in the breakdown. This represents the largest classified group in Ireland in 2018 and this is arguably due to the fact that Ireland was one of only very few countries in the EU at the time which allowed unrestricted access to the labour market to the nationals of the newest EU states (Quinn, 2010).

Germany, France, Italy, and Spain (the largest of the EU 15 before enlargement in 2004) have circa 12,000 of their citizens resident in Ireland. The final group included in the statistics from CSO Ireland are those migrants from the rest of the world, who account for 152,000 people living and resident in Ireland. They are represented as follows: Nigeria (17,000), Brazil (15,000), India (12,000), United States of America (11,000) and China (10,000). The remaining 50% of this group are made up of nationalities who have less than 10,000 citizens in Ireland, notable mentions include Mexico, Pakistan, New Zealand, and Australia who all have more than 5,000 people living in Ireland respectively. (See Table 1 on page 5).

The reasons behind the previously unprecedented immigration rates in Ireland in the last two decades can be underpinned by a two-fold explanation. Firstly, in the period 2000-2010, according to Turner

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(2015) and Quinn (2010), the immigration into Ireland could be explained by those countries who benefitted from EU enlargement post 2004, in the main, entering the Irish labour market in search of gainful employment in a prospering economy instead of targeting specific industries, in conjunction with Irish nationals and performing in roles that didn’t impact those in which Irish people worked – rather than “displacing” Irish nationals, immigrants are primarily working in low-skilled jobs (Turner et al., pp . 377:2015). This was largely representative of how immigration in Ireland functioned post 2004 and up until the full force of the economic crash was felt in 2010. Post-recovery, commencing around 2014 the second wave of contemporary immigration occurred where there were increased numbers of non-European nationals coming to Ireland for work and study purposes, for much the same reasons as during the ‘Celtic Tiger’ years where jobs were plentiful, the economy was booming, and salaries were amongst the highest in the European Union. This twinned with an increase in within EU migration to Ireland for work purposes in both lowly and highly skilled roles. This ‘second wave’ of immigration can be applied to the representative data in 2018 (Turner et al, 2015).

Table 1 – Estimated Population (‘000) living in Ireland classified by Nationality, 2012 - 2018

Year 2012 2013 2014 2015 2016 2017 2018

Nationality

Irish 4,047 4,081 4,118 4,153 4,189 4,226 4,264

UK 112 109 107 106 106 108 111

Rest of EU 15 ^(a) 51 53 57 60 65 69 74

EU 13 ^(b) 233 235 243 248 249 250 255

Rest of World 152 137 121 121 130 140 154

Total Persons (‘000) 4,594 4,615 4,645 4,688 4,740 4,793 4,857

a) Rest of EU 15: countries before enlargement on 1 May 2004, (i.e., Austria, Belgium, Denmark, Finland, France, Germany, Greece, Italy, Luxembourg, Netherlands, Spain, Sweden, Portugal)

b) EU 13: defined as 10 countries that joined the EU on 1 May 2004 (i.e., Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Slovakia, Slovenia), along with Bulgaria and Romania who joined on 1 January 2007 and Croatia who joined on the 1 July 2013.

Source: CSO Ireland*

*(The Central Statistics Office (CSO) Ireland)

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5 Literature Review

This part of the thesis focuses on the research to date on attitudes towards immigration among native- born individuals. It will address the contextual reasons and theoretical framework behind attitudes towards immigration and then proceed to discuss the individual determinants at a later stage of the literature review. Research on this topic is varied and broad ranging across a plethora of disciplines, touching on various theories and hypotheses in relation to why and how people have a particular attitude towards immigration. As such, here I focus on literature that covers attitudes towards immigration in a European context. I strive to reference literature which discusses the socioeconomic factors predominantly believed to impact these attitudes among the native-born population. Literature which posits potential explanatory reasons for the relationships between attitudes and socioeconomic status in a European setting are fundamental to this thesis.

Theoretical Framework of Attitudes Towards Immigration Group Threat Theory

Firstly, no discussion on the relationship between native-born persons of the destination country (majority group) and incoming migrants (minority) is complete without first discussing Group threat theory and its potential impact on the relationship between those who are native-born and in-migrants.

Initially proposed by Quillian (1995) in his book entitled ‘Prejudice as a Response to Perceived Group Threat’, this theory is based around the argument that when a group who is unfamiliar to the dominant or majority population comes into their area or territory it is a natural reaction for native-born people, in the case of immigration, to feel threatened and hold some form of animosity or resentment towards them at the outset at least. The collective threat is based on two factors, “the size of the subordinate group relative to that of the dominant one, and economic circumstances” (Quillian, pp. 5:1995).

The above theory and, indeed the basis for what constitutes prejudice for the purposes of this thesis, use Blumer’s definition of prejudice “as being a response to threats to the privileges of a group” (Blumer, pp. 3:1958). This may manifest itself most where competition is introduced into the equation, for jobs or the marketplace for example, and this, in turn, may have an adverse impact on in-group attitudes

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towards immigration in general – Outgroup size corresponds to perceived group threat, which relates positively to anti-immigrant attitudes (Schlueter et al., 2010).

Van Heerden and Ruedin (2019) conducted research on Group threat theory using data from various residential contexts in the Netherlands. They discuss how changes in the makeup of nationalities in various residential areas in the Netherlands is impacting native-born attitudes towards minority groups, from the perspective of Group threat theory (in this case the Ethnic threat effect) and Contact theory.

They allude to the fact that “competition over scarce resources, either material or cultural, reinforces in-group identification and strengthens out-group aversion” (Van Heerden, pp. 319: 2019). It goes on to say that this propagates a culture whereby existing networks easily feel threatened by the arrival of newcomers.

Another example of research conducted in relation to Group threat theory is that undertaken by Garcia- Faroldi (2017). While studying determinants of attitudes towards immigration on a Pan-European basis and in accordance with perceived Group threat theory, she expected attitudes towards immigrants to be increasingly negative in countries that have suffered more intense economic crises. In the findings, whilst it was concluded that countries facing a difficult economic situation tend to hold unfavourable attitudes towards immigrants, she could only partially state with reasonable statistical certainty that the percentage of foreign population in a destination country was significant, as Group threat theory states.

This is because, according to the author, other factors such as cultural proximity between immigrants and citizens of the host country are necessary and ought to be considered (Garcia-Faroldi, 2017).

Twinned with the countries who lie contrary to the postulated theory and evidence, for example Germany and Belgium, this accounts for ‘cultural and historical factors of both the host culture and that of the immigrants who settle there’. Quillian himself acknowledged this in the 1995 paper originally.

Finally, with reference to Group threat theory, Turner and Cross actually studied Ireland in a European context with a focus on whether attitudes towards immigration change or shift during hard times, as was their question for the paper. This thesis is not focused on the economic conditions of Ireland, but

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the underlying theories employed in this research paper are certainly relevant. Here, the authors highlight the fact that “much of the evidence on the formation of attitudes to immigration indicates that they are shaped by sociotropic concerns about national level cultural and economic impacts” (Turner et al., pp. 375: 2015). This is relevant as it directly addresses the two main components of Group threat theory and attributes much of the ‘creation’ of attitudes to these two factors. The results of this paper suggest that there was only a moderate change in attitudes to immigration in their studied time-period in general (2002 - 2010), with the exception of sentiment towards those of different ethnicity to the majority in Ireland as immigrants. Negative attitudes towards those of different ethnicity to the majority in Ireland actually declined the most of any European country in that same period. However, reverting back to how Group threat theory seems to have impacted this ‘shift’, Turner states in his conclusion that the perception that a person’s economic status could inordinately harm immigration is likely to increase opposition to immigration even further on a macro level (Turner et al., pp. 380, 2015).

Intergroup Contact Theory

The other main fundamental contextual determinant used to inform this thesis is Intergroup Contact theory. As first discussed by Allport (1954) and expanded upon by Pettigrew (1995), this theory “posits at its core that actual intergroup contact… may induce more favourable intergroup attitudes” (Schlueter et al., pp. 287: 2010). In essence the theory suggests that as immigrants spend more time, in larger groups, in the host country it is a natural human reaction that under optimal conditions – common goals, intergroup cooperation, equal status and authority support (Allport, pp. 6: 1954) – intergroup contact will ameliorate intergroup attitudes as a general rule. There is, of course, the argument that this contact could have the opposite effect and ‘deteriorate’ intergroup attitudes and critics of the theory use this as their primary platform. Schlueter’s main aim in the paper, in which he studies proportional outgroup size in a Dutch context, is to determine whether intergroup contact does have a positive effect on intergroup attitudes and finds that intergroup contact has a detrimental impact on anti-immigrant discriminatory intentions and disapproval of immigrants, mainly by reducing perceptions of group threat.

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Further studies on Intergroup Contact include Bridges and Mateut’s paper (2014), where they investigate determinants of attitudes towards immigration in Europe and link it to the race/ethnicity of the immigrants and how economic factors and intergroup contact impact these attitudes. Their findings suggest that the relative importance of these factors relies pivotally on the race/ethnicity of the incoming immigrant. In relation to intergroup contact, more exposure (to immigrants) appears to reduce opposition towards the arrival of different race/ethnicity immigrants, with little effect on those who are of the same as the majority group in a European, country-specific context. They argue that, essentially, people fear and are sceptical of what they do not know and it is therefore logical that the greater the levels of exposure they have with immigrants of a different culture or creed to them on a regular basis, the lower should be their opposition to further immigration.

Finally, and along the same lines in relation to intergroup contact theory, McGinnity et al., (2018) performed a comprehensive study around the topic of attitudes towards diversity in Ireland. This research encompassed a plethora of theories and logic on why native-born people have the attitudes they do on immigration, how they developed these beliefs and where, specifically, these belief systems are most prominent. The study focuses on social contact theory and notes that intergroup contact has the effect of ‘ameliorating’ threat perception, as all the other studies mentioned above point to conclusively. However, it stresses that the type/quality of contact as well as the quantity of contact is vitally important and references McLaren (2003), who states that ‘not all contact is positive’ (McLaren, pp. 915: 2003). The authors speak about the potential for reverse causality, namely that positive attitudes towards ‘out-groups’ may lead to increased contact with them whereas negative ones may lead to native- born individuals avoiding contact with the minority.

The aforementioned caveat is worthy of note as Barlow et al (2012) concluded that negative contact increases prejudice to a greater extent than positive contact diminishes it. So, if an in-group member has had a negative ‘experience’ with an out-group member in the past, this may well be the reason he/she chooses to avoid social contact with other members of the out-group in the future. This will have an increasingly catalytic effect compared to a previous positive experience of the same form, according

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to Barlow. This is an example of contact impacting attitudes, but the opposite may also hold firm and the ‘perceived’ negative experience could have been informed by the native-born respondent’s pre- conceived notions. McGinnity concludes in the paper as follows– where people who report “good”

quality contacts develop more positive attitudes towards immigration, it could also lead to people who already have positive attitudes towards immigrants becoming more inclined to report good quality contact and being more likely to frequent environments where contact with immigrants is more likely.

Other Factors associated with Attitudes towards Immigration

Another theory put forward by Macionis and Plummer (2008), based on economic factors, is that of the

‘scapegoat theory’, whereby they propose that it is human nature to find an avenue to avoid blame and people, therefore, are inclined to blame someone else for their own problems. This is particularly prevalent in times of financial instability and uncertainty they argue. Furthermore, such emotions may increase during times of crisis, inevitably laying the foundations for increasingly negative attitudes towards minorities in the host country (Hagenoorn et al., 2011).

Other ideological factors which have been proposed by researchers as potential explanatory factors for anti-immigrant sentiment move away from economic factors in part, an example of which is that as proposed by Saxton and Benson (2003), where they suggest that clusters of “right-wing ideology, old- fashioned racism and materialistic value-orientation provide a more cogent account of anti-immigrant sentiment than economic factors” (Jaime-Castillo et al., pp. 1090: 2015). Giugni and Koopmans (2007) similarly propose that the emergence and subsequent upsurge in radical, right-wing parties in parts of Europe is a significant contributory factor to negative attitudes towards immigration.

On the other side of this framework, Haubert and Fussell (2006) suggest that the globalised nature of the modern world is having a positive impact on general, global attitudes towards immigration. They highlight the positive effect of a cosmopolitan worldview as their paper was attempting to explain, at least in part, the reasons behind pro-immigrant sentiment in the UK during their studied time-period.

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10 Individual Determinants of Immigration Attitudes

On an individual level there has been extensive research done and published as to what are the main determinants of attitudes to immigration. Furthermore, how these determinants pertain to the various theories as discussed in the contextual framework section is of interest to this research. The primary focus of this thesis is explaining determinants of attitudes and, in particular, how the Group threat theory and Intergroup Contact theory can be applied and used in an Irish context.

Group threat theory, at an individual level, purports that as large numbers of the minority enter a nation, the majority are likely to feel threatened on both a cultural and economic level (Quillian,1995).

Competition for jobs, housing and resources will increase naturally due to greater levels of population from in-migration and, subsequently, is likely to lead to a sense of animosity and ill feeling towards the minority group. Those with lower levels of education and on lower incomes are especially susceptible to this phenomenon as they feel that the labour from the minority country will be directly competing with them across various facets of life. This, in turn, leads to negative attitudes towards immigration.

As stated earlier, where times are tough and the ‘immigrants taking people’s jobs’ rhetoric is all too prevalent, this sentiment and related attitudes become increasingly more negative in conjunction with the state of the economy deteriorating. The accompanying societal changes during periods of economic austerity dovetail with socioeconomic status to bring about these conditions. Interestingly, Jaime- Castillo (2016) takes this one step further and contends that the impact of socioeconomic status on attitudes toward immigration is larger in countries where social expenditure is substantial. The following paragraphs will address what different scholars have said on the topic and their rationale behind individual determinants of attitudes.

Facchini and Mayda (2006) wrote about individual attitudes towards immigration and split attitudes towards immigration into two distinct mechanisms – Scenario one suggests immigration has a larger impact on individuals at the top of the income distribution and scenario two proposes that low-income individuals are most impacted by influxes of immigrants. Scenario one would occur where per capita transfers are static, tax rates are adjustable, and a redistributive tax system is in place. This would place

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the burden of tax on the more affluent individuals if in-migration of lowly skilled immigrants were to occur and the affluent native-born population would be less favourable to immigration. However, the authors note that were the immigrants coming into the country highly skilled in the main then the reverse would be true.

Alternatively, scenario two concludes that where the taxes are redistributive and changes in the welfare state occur through alterations in per person welfare benefits with tax rates unchanged (Facchini et al., 2006), those who are less affluent will be more averse to immigration, regardless of skill level of the immigrant. The rationale behind this is that they will be in direct competition with in-migrants for jobs/housing etc and any potential welfare payments may also be impacted. Based on this theory and analysis, Facchini summarizes that the level of individual skill is positively correlated with pro- immigration preferences solely in countries where native-born individuals are, on average, more skilled than immigrants and individual income is negatively correlated with positive immigration sentiment.

In a similar vein, O’Rourke and Sinnott (2006) investigated individual attitudes towards immigration for 24 countries, based on socioeconomic and sociodemographic characteristics, and political attitudes of the majority group. The countries chosen were not continent specific and it was based on data released in 1995 by the International Social Survey Programme, with quite different migratory patterns in the EU compared to today. One of the more prescient conclusions which the authors made was that absence from the labour market (either unemployed, retired or voluntarily unemployed) matters little to attitudes to immigration, if at all. Secondly, highly skilled individuals are more positive towards immigration than low-skilled persons, while the association between skill and attitudes toward immigration are minimal in poorer and unequal countries compared to the association seen in richer, equal nations. Furthermore, O’Rourke concluded that attitudes towards immigration reflect nationalist sentiment which indicates that deep-rooted political and religious or cultural ideologies may be significant determinants of individual attitudes, predominantly negative, which are harder to identify and/or deal with over the course of time (O’Rourke et al., pp. 857: 2006).

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Butkus et al (2016) investigated the determinants of society’s attitudes towards immigration, similar to this thesis, with the distinction that it was a cross-national EU study and endeavoured to determine not only what influenced attitudes but also how do attitudes differ towards immigrants from the EU and non-EU immigrants. They stressed that although they could predict possible impacts of independent variables, they could not accurately anticipate what shapes attitude differentials pertaining to immigrants from both EU member and non-member states. The paper hypothesises that in relation to attitudes to immigration, people with a higher level of education, those who are employed, satisfied with their family’s financial situation and living in an urban setting are more likely to display positive attitudes, whilst those who are single, have children and are older are expected to be more negative.

Interestingly, Butkus et al., rejected the hypothesis that the proxy for income (being in gainful employment) statistically significantly impacts attitudes to immigration and they attributed this to the fact that people in general do not link their own labour market status with that of immigrants’ work status. However, on the contrary, those who feel downbeat in relation to their family’s financial situation are 1.5 times more likely to possess negative sentiments towards immigration than people who feel comfortable and confident about their family’s income (Butkus et al., pp. 300: 2016). Finally, with reference to education, the study concluded that with a higher level of education the probability of having positive attitudes towards immigrants rises, despite there being no difference in attitudes between primary and basic education. Furthermore, the results from Butkus’ research suggest that although people with tertiary education are more likely to support immigration in general than those without tertiary education, people in that classification are 0.6 times more likely to ‘support’ immigrants from other EU member states than immigrants from outside the EU.

Heath and Richards (2019) performed a cross-European study where they grouped 21 EU countries into three distinct ‘sets’ in their paper on European attitudes to immigration. Based on Blumer’s 1958 paper on ‘Collective Threat and Prejudice’, they aim to discover how each set view immigration on an individual level and then analyse how/why these sets differ from one another as well as identifying how countries within each set differ from others in the same group, as “Europe is a set of diverse diversities”

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(Heath et al., pp. 491: 2019). The study looks at both the sociodemographic and cultural features of the minority and majority group. Each set represented different viewpoints and outlooks in relation to attitudes to immigration. Set A (The Czech model) are categorised as the ‘restrictive’ group, Set B (The Irish model), represents the ‘selective’ group and Set C (Norwegian Model) are labelled the ‘open’

grouping. Generally, the criteria used to separate these countries was based on entry criteria, where Set C displayed positive attitudes in general and cared little for work skills, education, religion etc.

Members of the restrictive group seemed to pay little attention to religion/cultural factors but placed great emphasis on work skills and education of immigrant and Set B exhibited interest (statistically significant findings) across all measures of a migrants’ cultural and skill-based background.

In terms of sociodemographic characteristics of the majority and how it relates to this thesis, the findings are intriguing and suggest that in countries who have been previously categorised as ‘restrictive’, there is little difference between the attitudes of those with high levels of education/income in those countries and as such they share similar restrictive or negative views on immigration to their fellow compatriots and group members. Whereas, in Set B and C, the general public appear to be sharply divided by education and income. Heath points out that the Norway model in particular exhibits deep divides in terms of the restrictive/open divide and are the least consensual set as a result. Additionally, it is noted that countries which are less consensual regarding their attitudinal profiles are more polarised in terms of the social groups that typically display these attitudes. Meaning that the sociodemographic characteristic of an individual in any given country will not always yield the same views across attitudinal dimensions either, in theory.

One final and slightly alternative theory on individual determinants of attitudes was displayed in a paper by Paskov et al (2019). Social mobility is the comparison between a child’s level of success compared to their parents and is often measured based on numerous sociodemographic factors such as education, income and dwelling amongst others. This is relevant to this thesis as it is investigating social mobility in the context of attitudes to immigration and as social mobility studies the attainment of these sociodemographic ‘desirables’, it can be appropriately applied. According to Paskov, ‘a context of high

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upward mobility expands opportunities for all and might promote more positive attitudes towards immigration’. The background theory is that, at a micro level, those who are downwardly mobile and doing worse than their parents are assumed to be experiencing relative ‘deprivation and frustration’ that precipitates the flourishment of hostile, anti-immigrant attitudes (Lumpe, 2018; Paskov et al., 2019;

Varriale, 2019). This allies with the idea that the lower social classes are more likely to display negative attitudes towards immigration (Paskov et al., 2019).

Paskov et al use ESS data from 2014 as well as ESS-Devo Data to measure these attitudes. It finds that, whilst mobility on a contextual level may have an impact and the hypothesis cannot be rejected, the role of individual social mobility and its impact on attitudes provides little evidence of any association. The study tries to identify an “effect of social mobility on attitudes that is distinct from the effects of parental origin and later life destination” (Paskov et al., pp. 16: 2019). The authors did find some variations across countries however, with the likes of Lithuania, Turkey and Poland placing much more emphasis on the role of social origin and how it affects their attitudes to the minority compared to countries in Northern and Western Europe (Sweden, Finland, France, Netherlands) where social origin and mobility had little to no impact on how feel people feel about immigration.

Research Questions

In this thesis two main research questions are being tested related to attitudes towards immigration, one of which examines the determinants of these attitudes and the other focuses more on how or, in fact if, these determinants vary depending on the attitudinal dimension. Native-born individuals’ attitudes are the focus of this research as the thesis is aiming to capture how a non-immigrant from a non-immigrant background views immigration into “their” country across different aspects.

The structural changes and recent immigration characteristics of the Republic of Ireland described within this thesis provide these questions with an intriguing antithesis to previous research done on the topic. The rapid increase in Ireland’s immigration rate, the recent nature of the data being studied compared to other studies with reference to Ireland twinned with the impact of socioeconomic status on

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attitudes towards immigration from varying attitudinal dimensions makes this study distinct from other countries on similar topics. Therefore, the primary research question for this thesis is to discover:

I) Are socioeconomic determinants associated with attitudes towards immigration in the Republic of Ireland? focusing on 2018 as specified.

The second question relates to attitudinal dimensions and reads:

II) Does the association between socioeconomic status and attitudes hold across all attitudinal dimensions?

This thesis is striving to give insights into these questions by utilising and furthering the ideas studied in previous research. The focus, which past studies on the Republic of Ireland in relation to attitudes towards immigration have taken, was how the state of the economy and shifts towards being a destination country for immigration has seemingly changed these attitudes. This thesis diverges from this idea in that it investigates these attitudes across attitudinal dimensions in addition to socioeconomic determinants, as opposed to just concentrating on attitudes and how they have changed over time in line with the previously mentioned factors.

This study is much needed due to the fact that Ireland has experienced much inward migration in recent years, which makes it a perfect country to analyse for immigration purposes. It would assist policymakers in making informed decisions on immigration as regards what elements of immigration are considered by its citizens as positive or negative for the country and what aspects are important for the people. In addition, the recent shift in immigration patterns into Ireland, namely the places where people are coming into the country from, may have impacted the way people view immigration and future studies could use the results of this year-specific study to compare attitudes and analyse how they have changed over time.

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16 Hypotheses

The three hypotheses for this thesis are informed by Group threat theory and Intergroup Contact theory as outlined in the Literature Review. The determinants of attitudes towards immigration in Ireland are based around these theories and previous research which suggests that those who are without tertiary education and on low-incomes are more likely to be negatively inclined in their attitudes towards immigration. The logic is that, as Group threat theory proposes, where the minority is competing with the majority over scarce resources, housing and jobs, it is a natural consequence of competition that negative attitudes towards immigrants materialise in such conditions, particularly with regard to economics and the procurement of stable financial livelihoods. In scenarios like this, those individuals who are highly educated have the prerequisite ‘skills’ to obtain highly skilled and well-paid jobs, thus taking away their perceived need to ‘compete’ with the minority groups in the same way as someone who doesn’t have tertiary education or on low-income is required to do. For this reason, it is proposed that:

(H1) Individuals without tertiary education will be more likely to oppose immigration across all dimensions of attitudes to immigration, all else equal.

(H2) Individuals on low incomes will be more likely to oppose immigration across all dimensions of attitudes to immigration, all else equal.

As will be explained in the data section below, this thesis is using questions related to three distinct attitudinal dimensions and aims to examine the association between attitudes towards immigration, across these attitudinal dimensions, and socioeconomic status of native-born people in Ireland in 2018.

One of the dimensions refers to the perceived effect of immigration on the economy. As stated above, finances and money matters in general weigh heavily on people’s mind on a daily basis and it logically follows that it will have an impact in some form when it comes to people’s way of thinking with regard to attitudes towards immigration, the research suggests. Intergroup contact theory purports that the more exposure the majority have to the minority, when these experiences are largely positive this will have a beneficial effect on attitudes and provide a platform for native-born people to be more open to

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immigration in general. Negative encounters with minority groups have a less detrimental effect on attitudes many studies have proposed in addition (Allport, 1954; Schlueter et al., 2019; van Heerden et al, 2019). This is relevant to the final hypothesis as it may imply, in turn, that intergroup contact and subsequent harmony or issues which occur do not impact native-born attitudes towards immigration quite as much as economic matters. Therefore, twinned with the perceived economic threat as discussed earlier, the third hypothesis implies the following:

(H3) Individuals will be more likely to oppose immigration due to the perceived negative effect of immigration on the economy when compared to the perceived impact of immigration on cultural life and Ireland as a place to live, all else equal.

Data and Method Data

The data I will be using for this thesis is from the European Social Survey (ESS). There are nine waves of surveys which began in 2002 and are taken bi-yearly, with the most recent round of survey questions published in 2018 (at the time of writing). The survey questions are administered by National Coordinators in each nation, under the remit of ESS specifications, one year in advance of publications and the questions are asked of people from various European countries, who are selected at random using the Random probability sampling. There are more than 30 participating countries. The interviews are conducted by means of a face-to face interview and the various waves are not longitudinal, meaning that each round is a unique, previously unstudied batch of respondents who make up a representative, cross-sectional sample. The minimum sampling age is 15 years old, with all respondents above this age minimum, and no upper age limitations. The survey’s primary aim is, according to the ESS website, to “measure the attitudes, beliefs and behaviour patterns of diverse populations in more than thirty nations” (www.europeansocialsurvey.org, 2020).

The range of questions within the survey are broad and are intended to gain an understanding of European people’s views and opinions on social, political, economic, and moral issues which are part

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of living in Europe today. Survey questions are updated and amended as society develops and any changes made to questionnaires from wave to wave are coded and displayed accordingly so they flow and can be compared year on year for research purposes. The people surveyed by the ESS are intended to be representative of the average citizen, resident within private households in each country and no discrimination is made in terms of race, creed, religion, nationality, citizenship and/or legal standing within the country. The citizen needs to be a ‘resident’ of the participating country, while ESS rules guidelines state that all countries must aim for an ‘effective achieved sample size’ of 1,500 (or 800 in a country with less than 2 million people). Substitution of non-responding households is not permitted (www.europeansocialsurvey.org, 2020).

Bearing this in mind, this thesis uses the latest wave of data, round 9, to portray an accurate and as up to date as possible representation of attitudes and beliefs in The Republic of Ireland towards immigration. I do not strive to compare timepoints and differences in attitudes between rounds as my sole focus is to comment on socioeconomic status shaping attitudes in 2018. As I am examining the impact of socioeconomic status of Irish citizens on attitudes towards immigration specifically, I have chosen to exclude individuals in the sample who were not born in the Republic of Ireland. This also excludes those born in Great Britain and Northern Ireland who hold Irish citizenship and live in the Republic, to ensure that the native-born’s socioeconomic status is all that I am capturing in my analysis as appropriate. Round 9, the fieldwork of which was completed between September 2017 and January 2018, consisted of 2,216 respondents at the outset, with 1,821 remaining after I removed those not born in Ireland. 393 respondents said they were born in another country, with two further respondents refusing to answer the question, and as such they were removed for testing purposes. Further cleaning of dependent and independent variables removed another 55 cases which represented missing responses, so the final number of respondents for the study is 1,766.

Ethical Considerations

As individual level data is being dealt with, confidentiality of respondents is of the utmost importance.

This is especially important when dealing with financial and social characteristics of respondents, as

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this thesis and data does, and so this has been taken into consideration. Prior to allowing access to the data to researchers, all respondents were de-identified and the data was checked in this regard by the ESS Core Scientific Team (CST).

Participation in ESS studies emanates from informed and voluntary consent and this is reasonably presumed. The respondents’ identities are anonymous, their security and privacy are respected at all times and the outcomes of the analysis in this thesis do not allow for re-identification of participants, for any reason, by anyone who subsequently accesses the data. As all of the data being used for this thesis is secondary data, and no direct contact has been made with any of the respondents due to the de- identification process, it can be assumed that the use of the data has not caused any damage or anguish to any of the respondents.

The dataset which is being used to perform the analysis is being downloaded directly from the ESS website using my own personal researcher login, provided to me by the University, whereby it is required that informed consent be given in relation the potential sharing and future use of the data. The subsequent statistical testing undertaken is being done through the STATA software package. No weights are to be applied to the dataset due to the fact that country to country data is not being compared and the data has not been altered in any way other than the recoding as explained below in the methodology section.

Variables

Dependent Variables

There are a number of questions in the ESS questionnaires related to immigration and the perceptions of native-born individuals towards various types of migratory behaviour and patterns, with minor variations in wording from round to round, with the nucleus of the query remaining constant throughout all versions of ESS research publications. This thesis is based around three primary questions in relation to attitudes towards immigration, of which all three are the basis for my dependent variables from my research design. These chosen variables represent views on immigration across three broad, but varied,

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attitudinal dimensions and as such form the basis for my secondary research question and each hypothesis. All the outcome variables refer to the impact that the arrival of immigrants and immigration in general has on various aspects of society in the Republic of Ireland, from the perspective of native- born citizens. Initially, the outcome variables selected were all on the Likert scale and so can be deemed categorical, specifically ordinal, in scale. They were all subsequently recoded, split into four groupings in the first instance for the descriptive statistics and initial analysis. Finally, they were made binary for the purposes of performing a logistic regression with a strictly positive or negative response, hence the reasoning for not analysing them on the original continuous scale. Further rationale behind this decision to treat my variables as explained was that people’s response style differ from respondent to respondent regarding ten-pointed scales ranging from disagree to neutral to agree, and so a clear ‘for’ or ‘against’

response was needed with less ambiguity. Hence the reason for not proceeding with an estimated OLS regression on the categorical variables, for example, and proceeding with a logistic regression instead.

Firstly, respondents were asked their opinion on whether immigration is good or bad for the country’s economy. They were given ten response options, which ranged from ‘0’ and ‘Bad for the economy’ to

’10’ and conversely ‘Good for the economy’. 1-9 represented the same, with lower values pertaining to attitudes which exhibit increasingly negative impacts of immigration on economic prosperity, whereas higher values represent the view that immigration ameliorates the country’s economy. Missing values and respondents who refused to answer the surveyor’s question were all removed from the research as these cases represented an insignificant number which would have had little to no impact on the results or subsequent analysis undertaken in the thesis in relation to the research question. As a result, these variables will not be recategorized. These ‘missing’ values accounted for only 2 cases and were dropped subsequently. Once this process was complete, I recoded and relabelled the first dependent variable by categorising respondent’s attitudes into four groupings at this juncture in order to move towards a more unambivalent response, where respondents are classified as being predominantly positive or negative in their attitudes towards immigration. These groups were based on negative (0-4), neutral (5) and positive (6-10) responses (The response option of 5 was chosen as the ‘neutral’ response as it represented the true midpoint value between 0 and 10). A fourth category labelled as ‘don’t know’

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pertains to a portion of respondents who were unsure of their feelings on the impact immigration has on economic matters and was kept as they represented almost 3% of the entire sample. Perceived impacts of immigration on the economy were coded as follows: 1 “Detrimental to economy 2” Neutral 3” Good for economy 4” Not sure.

In similar fashion and nature to outcome variable 1, outcome variables 2 and 3 relate to native-born viewpoints on whether or not ‘immigration undermines or enriches the cultural life of the country’

(Outcome Variable 2) and a more generally phrased and framed question, ‘do immigrants make the country a worse or better place to live’ (Outcome Variable 3). Again, the scale ranges from 0 -10 with the negative attitudes towards immigration’s affects displayed for each respective question in the low values, and the more positive and open attitudes towards influxes of people into the Republic of Ireland amongst the higher values, in that numerical range. Like in outcome variable 1, to maintain consistency across all of my outcome variables, I recoded and relabelled the respondent’s answers into four distinct groups for a more unambivalent and firmer positive/negative response. For outcome variable 2, the groups took the following form: 1 “Undermines cultural life 2” Neutral 3” Enriches cultural life 4” Not sure. The recoding was identical to the previous variable and similarly I removed any refusals or missing answers, which represented only one response in outcome variable 2. As regards outcome variable 3, four unique groupings were coded identically and labelled as follows: 1 “Worse place to live 2” Neutral 3” Better place to live 4” Not sure. There were no missing or spoiled responses to this question and so no additional cases were dropped from the study.

The recoding of the outcome variables culminated in each one being made binary for the final, logistic regression. This was done by combining the neutral and positive responses together, dropping the grouping whose responses were non-committal, and placing the negative answers alone. This element was conducted in order to capture purely negative responses from my outcome variables with regard to attitudes towards immigration when tested against the primary socioeconomic determinants and controls. All dependent variables selected will be, therefore, be analysed with respect to the fact that they are binary in nature after these changes have been made.

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22 Independent Variables

There are a number of variables which are available from the ESS which can be utilised to examine the association between attitudes towards immigration and socioeconomic status of natives, across different attitudinal dimensions. In this thesis, as the two primary hypotheses relate to education and income, the first two and therefore primary independent variables chosen here provide us with information on both of these factors. This is apt as it is widely accepted that socioeconomic status, and particularly education and income, are factors which influence opinion on immigration and they have been widely studied in relation to this topic. Regarding the first variable, eisced, the education variable selected here tells us the level of the respondent’s education, ranging from 0” and less than secondary education to 7” which pertains to those surveyed with higher tertiary education. There were six respondents who gave an answer other than one of the seven options, and as such they were excluded from testing for the purposes of the analysis due to the immaterial quantity. One respondent refused to answer, and another did not know their educational level and they were also dropped from the dataset. Recoding of the variable took the form of classifying respondents into two clusters. The first cluster represented those without tertiary education, coded 0” without tertiary education and the second cluster was those surveyed who had partaken in and completed some form of tertiary education, coded 1” tertiary educated. Post-coding this variable is treated as binary as such, with 0 representing no tertiary education and 1 signifying a tertiary educated individual.

The second independent variable being used for analysis here is wealth related, entitled income decile, and as the name suggests relates to which income class each household belongs or fits based on their self-reported household income from all sources. Income decile is being used as a proxy for wealth, a commonly used indicator of socioeconomic status. There are 10 income deciles or groups in which people were originally classified. These deciles were created by each respondent declaring their self- reported household income and, their answers were subsequently re-categorised into distinct ‘deciles’, ranging from the lowest income decile, 1”, to the highest income decile 10”. For the purposes of this research this variable was then recoded and made categorical in nature by splitting each grouping into three quantifiable income classes – Low, Mid and High-Income earners. Those in Income decile 1”, 2”

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and 3” were reclassified as low-income respondents, those in decile 4”, 5”, 6” and 7” are now considered to be average income recipients and all those 8” or above are high-income earners. A fourth grouping, which consists of those who chose not to respond or did not know how to answer the question, was also reclassified and included in the initial analysis in the descriptive statistics section as they represented around 30% of the entire sample, to be analysed at a later stage, and named “Inconclusive”.

Three of the four remaining control variables are commonly used in demographic analysis and have been selected as they represent appropriate control variables for this research question. They are all either socioeconomic variables in and of themselves or related in terms of socio-demographic characteristics. The first of these is gender and is a binary variable where 0” refers to the respondents’

gender as male, 1” tells us that the person surveyed is female. There were no missing values or anomalies to drop here. Secondly, the age of the respondent was used to control for any attitude variations which seemingly differ based on age group. The ages of respondents ranged from 15 to 90 years old, with a few respondents’ ages being unavailable and these cases were excluded and dropped from the study consequently. This variable was recoded into four distinct age groups so that it is categorical in nature as follows: 1” 15-25 years old 2” 26-39 years old 3” 40-59 years old 4” 60+ years old.

The third variable included in testing, which again was chosen having read previous literature and its inclusion is almost universal when discussing this topic, is the Urban/Rural impact on attitudes towards immigration. In this ESS Round 9, this variable is referred to as domicile, and constitutes five options.

These options are: 1” A big city 2” Suburbs or outskirts of big city 3” Town or small city 4” Country village and 5” Farm or home in countryside. To make the later analysis and interpretation as clear as possible two missing observations were removed from the dataset and the variable was recoded to then display a binary variable, where 0” pertains to the Urban population and 1” represents the Rural population. Urban respondents are those in Groups 1, 2 and 3 in the original domicile variable, rural respondents are those who were classified as 4” and 5”.

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The final independent variable selected is socioeconomic in the sense that religion is widely considered to be a contributory predictor of wealth attainment. The primary justification for including religion here is, however, that it may affect attitudes towards immigration. Additionally, religion in particular was chosen as it has not been used incredibly often in past studies on this subject in general. It is of further relevance given the history and influence of religion in society in the Republic of Ireland in general. As a result, it can provide an interesting opportunity to study its impact on the dependent variable in this thesis. The aim here is not to differentiate between religions and their association with the dependent variable but rather to identify if the prevalence or lack of religion in people’s lives is associated with their attitudes towards immigration across attitudinal dimensions. The question asks respondents whether they belong to a specific religion or denomination, with only ‘yes’ or ‘no’ as available responses. There were 8 ‘don’t know’ or ‘refusal’ answers and they were dropped from the study as per previous variables.

Methodology

There are three primary hypotheses in this thesis, based around two main research questions. H1, H2 and H3 were tested using a combination of descriptive statistics and logistic regressions. Crosstabs and multivariate analysis have been employed to determine whether an association exists between my three dependent variables and independent ones, as intimated in the original hypotheses. Three logistic regressions were employed as a means of introducing my other independent and control variables and analysing if the inclusion of these variables has a statistically significant impact on the original relationships. I have included the ‘Not Sure’ responses from the dependent variables in the descriptive statistics for illustrative purposes, but they have subsequently been removed in the main analysis in order to make the interpretation of the regressions hierarchical in nature. This was also done with the

‘inconclusive’ responses from the ‘income’ independent variable. The subsequent cases in the dataset then stand at 1,250. This compares with the previous number of 1,766 cases prior to the removal of ‘Not Sure’ responses for the purposes of regression analysis. The regressions will then tell us the extent of the relationship. Additionally, it will allow us to determine if an extra control alters the significance or

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influence of another independent variable on the outcome variable. To clarify this final part, I have employed a logistic regression model when testing the hypotheses for analytical purposes.

The conditions for logistic regressions must be met to perform this type of testing. Regarding the manipulation of the variables, in order to fulfil the assumptions of logistic regressions, I have recoded my outcome variables in order to make them binary in nature. All negative responses are coded 0”, whereas positive and neutral responses are grouped together and coded 1”. The chosen independent variables are uncorrelated with the error term and indeed with one another in order to avoid multicollinearity. Pearson’s correlation coefficient test was done to ensure this. The explanatory variables were all chosen as (i) the literature suggested they had an association with the selected dependent variables and (ii) because each of them was unique and distinct from each other while still providing relevant and interesting data and findings on the associations being tested. Furthermore, the error term has constant variance, which fulfils the requirement of homoscedasticity.

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26 Results

Descriptive Statistics Dependent Variables

Table 2 gives a broad overview of the perceived impact of immigration into Ireland across various attitudinal dimensions regarding life in Ireland, encompassing both social and economic factors.

Table 2 – Perceived Impact of Immigration into Ireland across attitudinal dimensions, in % terms of total respondents Attitudinal Dimension Economy Cultural Life Place to Live

Detrimental to the

Economy 23 % - -

Neutral 18 % - -

Good for the Economy 57 % - -

Unsure of the impact 2 % - -

Undermines cultural

life - 24 % -

Neutral - 17 % -

Enriches cultural life - 57 % -

Unsure of the impact - 2 % -

Worse place - - 20 %

Neutral - - 19 %

Better place - - 59 %

Unsure of the impact - - 2 %

Total Respondents 1,766 1,766 1,766

Source: European Social Survey *(ESS) Data on Ireland, 2018

* (The survey measures the attitudes, beliefs, and behaviour patterns of diverse populations in more than thirty nations across Europe)

Table 2 tells us that over 50% of all respondents display favourable attitudes towards immigration in relation to their response on the impact of immigration with regard to each distinct attitudinal dimension. 59% of respondents said that they feel Ireland is a better place to live due to immigration, which represents the most favourable response across all attitudinal dimensions. Almost a quarter of respondents believe that immigration undermines cultural life on the island. Interestingly, this figure is

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comparatively larger than the 20% or 360 respondents who feel immigration makes Ireland a worse place to live. The neutral responses are, by in large, quite similar across the three attitudinal dimensions (17% - 19%), as are the answers where respondents are unsure of the perceived impact of immigration across the various dimensions (1% - 2%).

Independent Variables

With total respondents amounting to 1,766 in total, the following two graphical representations illustrate the breakdown of these respondents, according to educational level (Figure 1) and income level (Figure 2), as a percentage of total respondents surveyed.

Figure 1 – Breakdown of Primary Independent Variables - Educational Level of Respondents

Figure 1 displays information relating to one of the primary independent variables used for analysis in this thesis – Educational Level of Respondents. As we can see from the above, the largest group within the 1,766 respondents are those without tertiary education, amounting to 1,339 people or 76% of respondents. The smallest grouping are those respondents who have, at least, a tertiary level of education. This group accounts for 427 people or 24% of total respondents surveyed.

76%

24%

Educational Level of Respondents

% of Respondents without Tertiary Education % of Respondents with Tertiary Education

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Figure 2 – Breakdown of Primary Independent Variables - Income Level of Respondents

Furthermore, we can see from Figure 2 that the income level of respondents is fairly evenly split across low and mid-income, with 553 respondents (31%) reporting low-incomes and 490 people (28%) identifying with the mid-income bracket. However only 13% or 235 respondents were categorised to fit into the highest income grouping.Respondents who failed to identify their income level to surveyors amounted to 488 people (28%), the majority of whom (55% of the 488 respondents) were without tertiary education and of retirement age or in high school and under the age of 18, according to the data.

Dependent/Independent Variable Relationship Testing

Perceived Impact of Immigration, across attitudinal dimensions, by Education Level

The first of the two main independent variables proposed as a primary determinant in this thesis is Educational attainment. The below graphical representations illustrate the perceived impact of immigration, across attitudinal dimensions, with respect to the education level of the native-born respondent.

31%

28%

13%

28%

Income Level of Respondents

% of Respondents on Low-incomes

% of Respondents on Mid-incomes

% of Respondents on High-incomes

% of Respondents who responded inconclusively

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Figure 3 – Perceived Impact of Immigration on the Economy with respect to Educational Attainment of Respondents

Figure 3 displays the association between educational attainment and the perceived effect of immigration on the economy. The results indicate that 28% (375 people) of respondents without a tertiary education feel that immigration is detrimental to the economy and hinders its growth.

Comparatively, only 8% of those with a third level qualification feel that immigration is harmful to the Irish economy. On the contrary, just over 75% of respondents surveyed with a tertiary education believe that immigration was in fact beneficial and a positive thing for the country’s economy. This compares favourably to those without a tertiary education, where marginally more than 50% of people are of the opinion that immigration boosts the Irish economy. Those who believe immigration is neither good nor bad for the economy stands at 19% for those with less than tertiary education, and around 15% for those with a College, University or Third level qualification.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

Detrimental to Economy Neutral Good for Economy

Perceived Impact of Immigration on the Economy

Without Tertiary Education Tertiary Education

Socioeconomic Status And Attitudes Towards Immigration In The Republic Of Ireland