Economic and non-economic determinants of attitudes towards immigrants in Thailand
Rachael KAWASAKI and Yuichi IKEDA
Abstract: This study uses survey data from the 2013 World Values Survey inThailand to examine the economic and non-economic determinants of attitudes
towards immigrants in a newly industrialized, non-Western country. Using anovel method of selecting non-economic variables, this model improves onprevious models of attitudes towards immigrants. In contrast to previous research,
individual skill level was not found to be significant in determining attitudes
towards immigrants, suggesting that previous research may have been overbiased
towards developed countries. Rather, non-economic variables were found to bevery significant in determining respondents’ attitudes. These variables include
perceived threat and group identification, institutional trust, beliefs about
individual agency, and adherence to norms and tradition. Future research will
extend the study to include up to 60 countries, allowing for a community analysis
which fully delineates the different determinants of attitudes towards immigrants
globally.
1.
Introduction
International migration is a growing global phenomenon, both in sheer numbers andscope of sending and receiving countries. While migration has always figured in humanhistory, today immigration has led publics and governments to critically reexamine who
belongs, what rights are to be guaranteed, and how different religions, ethnicities, andcultures can coexist. In Europe, it is clear that attitudes towards immigrants and immigration
have taken an organizing role in populist party platforms, but what is not clear is why(Lesinska, 2014). Theories generally cite three possible causes: economic competition,
cultural backlash, and political demography (Dennison, 2019), but theoretical gaps remain.
Notably, when do economic considerations, such as immigration’s effect on the labor market
or the government’s fiscal burden, take precedence over an individual’s cultural preferences?
Understanding the determinants of attitudes towards immigrants and immigration isessential for creating favorable and effective economic and social policies. When economic
factors are dominant in determining people’s attitudes towards immigrants and immigration,
attitudes can be an indirect measure of the distributional effects of immigration and help
identify those who are being economically harmed by immigration. If attitudes towards
immigrants are determined by cultural or individual factors, policymakers may instead electto choose a public information campaign or reexamine their immigrant integration policies.
Finally, attitudes towards immigrants have a profound impact on immigrants, including theirsocial and economic integration (Constant et al., 2009) and physical and mental health(Pernice and Brook, 1996; Gee et al., 2007; Agudelo-Suarez et al., 2009). Discriminatory
practices against immigrants undermine the rule of law, waste human capital, and can lead tosocietal tension. Countering these practices and ensuring the rights of immigrants in a
destination country should be of equal importance to policymakers.
One of the most glaring gaps in the research on attitudes towards immigrants andimmigration is the overrepresentation of developed, Western countries.1 Research tends tofocus on the movement of international migrants from less developed countries to developed
countries, from non-Western countries to Western countries. While high-income countries
Here, “Western countries” is intended to mean European countries and settler countries (Australia, Canada,
New Zealand, and the United States). Overall, the majority of cross-national studies focus on these countries(Ceobanu and Escandell, 2010).
1

remain some of the most popular destinations for immigrants in the world, the percentage ofinternational migrants living in the less developed countries is sizable, at around 43 percent
or 112 million people (UN DESA, 2017). Furthermore, the regional destinations ofimmigrants are changing. From 2000 to 2017, Asia added more international migrants thanany other region as well as experiencing the largest percent growth. The total migrants in theregion increased by 60 percent (UN DESA, 2017). Despite these changes, studies on attitudes
towards immigrants and immigration often assume a Western cultural and political context,
rendering a full, cross-cultural understanding of attitudes towards immigrants as incomplete.
This study aims to remedy this oversight by modeling the determinants of attitudes
towards immigrants in Thailand, a non-Western, newly industrialized country. In 2017,
Thailand hosted the 17th largest number of international migrants in the world, with anestimated 3.6 million international migrants residing in its borders (UN DESA, 2017). Like
many of the European countries studied, large-scale migration to Thailand began in the postwar period and includes both economic migrants and refugees fleeing persecution. Migrants
also tend to be low-skilled, generally employed in manufacturing, construction, agricultural,fishing and seafood processing, and domestic work (IOM, 2019). However, in other aspects,
Thailand and its migration flow differ dramatically from the countries generally studied inresearch on attitudes towards immigrants. First, it is a constitutional monarchy with apolitical system dissimilar to the liberal democracies usually surveyed. Furthermore, it is a
newly industrialized country, having reached upper middle income status in 2011. Finally,
while Western countries generally have a mix of migrants from both developed and lessdeveloped countries, the vast majority of Thailand’s international immigrants come from theless developed, surrounding Mekong countries. Thus, migrants and natives often share thesame religion and race, though historic animosities remain.
By comparing the determinants of attitudes towards immigrants in Thailand to theprevious research, this study corroborates some of the dominant theories of how attitudes areformed, namely intergroup conflict theory. However, this study’s findings also contradict
several previously established patterns. The finding that educational attainment is dominant
in determining attitudes, suggesting that the extent to which education affects people’s
attitudes towards immigrants may be culturally or regionally dependent. Determinants related
to institutional confidence also show results that seem to be contrary to trends in Westerncountries. Finally, this paper contributes new insights into how beliefs about agency andcontrol can be salient determinants of attitudes. This model represents an overall
improvement in terms of fit as compared to previous cross-national models.
2.
Literature Review
Studies have found various key factors in determining individuals’ attitudes towards
immigrants and immigration. On the individual-level, determinants of attitudes can be split
into economic and non-economic variables. The overall economic and political situation havealso found to have an effect on individuals’ attitudes. In general, most studies conclude thatthese factors work in concert to determine an individuals’ attitude towards immigrants.
For economic factors, the highest education attained is often used to measure theindividual’s skill level. Education has been shown to have a strong, inverse relationship with
anti-immigration views (Mayda, 2006; Scheve and Slaughter, 2001; Dustmann and Preston,2006). Lancee and Sarrasin describe the relationship between education and more inclusive
attitudes towards immigrants and immigration as “one of the, if not the, strongest and mostconsistent predictor of host country citizens’ attitudes towards immigrants” (Lancee andSarrasin, 2015, pp. 1). According to Mayda, Scheve and Slaughter, and Dustmann and
Preston, education measures the skill level of the respondent and can, thus, be compared tothe skill level of immigrants to determine whether or not the respondent is in labor market

competition with immigrants.2 For this reason, tertiary-educated individuals in European andsettler countries are rarely in competition with the majority of immigrants and, therefore,
have more positive attitudes towards immigrants. Mayda (2006) finds that while both
economic and non-economic factors are significant in determining people’s attitudes,
economic factors have a larger effect on people’s attitudes in the nearly 44 countries
surveyed.
Another economic factor believed to have an effect on individuals’ attitudes towards
immigrants is the perceived effect of immigration on fiscal burden. Between countries, thepublic in countries with more comprehensive welfare systems was found to have a more
inclusive attitude towards immigrants and immigration (Crepaz and Damron, 2009;
Hainmueller and Hopkins, 2014). On the individual level, respondents who are at greater risk
for tax increases are more likely to have negative attitudes towards immigrants andimmigration. In this case, these individuals are natives with higher incomes in states withmore a more generous social safety net (Hanson et al., 2007). As such, there could be abalancing effect between labor market competition and a rise in taxes, as higher income andhigher skilled individuals are less likely to be in competition but more likely to pay throughhigher taxes (Hanson et al., 2007).
While models may find that economic factors are dominant, a number of non-economic
factors are often found to contribute to individuals’ attitudes towards immigrants. First, ahigher value on cultural homogeneity are correlated with more negative attitudes towards
immigrants (Sides and Citrin, 2007; Mayda, 2006). While others may see immigration as away to enrich the national culture, other respondents find it a threat to the cultural identity of
the country. Those respondents who are more likely to identify as being on the political rightwere also more likely to have negative attitudes towards immigrants and immigration (Mayda
2006; Malchow-Møller and Skaksen, 2008). People who identify as religious are more likely
to have more inclusive attitudes towards immigrants and immigration (Daniels and Von DerRuhr, 2003). Finally, demographic factors have been found to be related to attitudes towards
immigration, such as age, gender, and whether the respondent lives in a rural or urban area
(Mayda, 2006; Gorodzeisky and Semyonov, 2009; Quillian, 1995).
Intergroup conflict theory can help explain both the economic and non-economic
factors which determine attitudes towards immigrants (Campbell, 1965; Sherif, 1966; LeVine
and Campbell, 1972). Group theory posits “that prejudice and discrimination are often basedon conflicts of interest between groups” (Esses et al., 1998). Group conflict can be separated
into perceived threats to material or symbolic resources. In the case of realistic groupconflict, group conflicts occur over real competition over scarce resources, for example, overa limited amount of employment for certain groups. In contrast, social identity theory statesthat individuals categorize other into either outgroup (those who are different fromthemselves) and ingroup (themselves and those who are similar to them). Limiting theopportunities of those in the outgroup becomes one strategy to increase the distinctivenessand cohesion of the ingroup (Esses et al., 1998). Thus, through exclusion of members of theoutgroup, the ingroup can fend off perceived threats to their symbolic resources, in this casethe positive identity gained from the group. Therefore, those who identify more heavily witha group are likely to have more hostile feelings towards outgroups. And last, it is important tonote that group conflict is caused by a perceived threat to one’s group. While in the case ofrealistic group theory this threat is true, a threat does not have to be realistic in order to cause
conflict, and individuals more sensitive to threat should have stronger reactions.
2

Some scholars, however, dispute the use of education as a measurement of skill and only skill, arguing that
education is too highly correlated with cultural values that can also determine attitudes towards immigrants, e.g.
reduced authoritarianism (Hello et al., 2007) and an emphasis on cultural diversity (Davidov and Meuleman,2012).

3.
Methodology
Data for this study was taken from the World Values Survey Wave Six conducted in
Thailand in 2013. A total of 1200 people were randomly surveyed. Because few immigrants
were surveyed (around 1 percent of the sample), immigrants and the children of immigrants
were eliminated from the sample. The dependent variable is derived from the following
question:
V46. When jobs are scarce, employers should give priority to people of thiscountry over immigrants.
[1] Agree[0] Neither *originally coded [2][0] Disagree *originally coded [3]Respondents who had protectionist views were coded as 1, and those with more inclusive
views or uncertain views were coded as 0. Protectionist, in this case, is used to mean the viewthat the domestic labor market should be protected from foreign competition in the form of
migrants. This usage is not common and is used here because of its expediency. While thequestion involves considerations about the economic impact of immigration, it asks whether“employers” and not the government should intervene in hiring immigrants. As such, thisdependent variable does not measure attitudes towards immigration and immigration policy,
but rather attitudes towards immigrants and the acceptability of employment discrimination
against them (see Ceobanu and Escandell, 2010). Mayda’s model used a different dependent
variable, which measured people’s attitudes towards immigration policy; however, thisquestion was retired from subsequent World Values Survey waves. Overall, amongst the1120 native respondents, 62.9 percent held protectionist views with regards to employing
immigrants.
Demographic variables were chosen according to Mayda’s (2006) model. The
economic variable used was highest education attained. This variable was chosen because it
is a proxy for skill level and, thus, determines whether or not respondents are in economic
competition with the mostly low-skilled immigrants to Thailand. While the World Values
Survey asked questions related to income and social class, these variables were included as
demographic factors instead of economic factors because they require the respondent tosituate themselves within the larger society. For example, question 239 asks “On this card isan income scale on which 1 indicates the lowest income group and 10 the highest income
group in your country. We would like to know in what group your household is.” This
question asks a subjective question, one which asks the respondent to imagine the society as awhole and where they might be located. As a result, highest education was chosen as the
economic variable because it is an empirical measure of skill.
Finally, non-economic variables were chosen according to the following method.
First, Spearman’s correlation was employed between the variables to find variables that werehighly correlated (rho greater than or equal to absolute value of 0.75). Then the variables
were regressed against the dependent immigrant variable. Of the correlated variables, thosewith the lowest AIC were selected while the others were eliminated. As a result, 9 variables
were eliminated, leaving 158 non-economic variables. Following this step, a chi-squared test
was performed to show the correlation between each variable and the immigrant dependent
variable. Only the variables that were significant at the 5% level were selected, as theseshowed that there was an unequal distribution of the responses to the variable question andthe immigrant dependent variable. Continuous variables were then regressed against the
proportion who felt that employers should discriminate against immigrants during tougheconomic conditions. The purpose of this step was to ascertain which variables showed aclear trend on how people answered the dependent variable. Continuous variables werevariables with four or more possible responses, as these questions were ordinal. From thisstep, 80 variables were eliminated. As a result, a total of 29 continuous variables and 25 noncontinuous variables were selected for multiple logistic regression. By using this method,
non-economic variables with a clear relationship with the dependent variable could be found,even if they were not commonly associated with attitudes towards immigrants in previous
literature.
Table 1. Method of selecting non-economic variables
1. Eliminate demographic and economic variables [167 variables]
2. Spearman’s correlation [158 variables]
3. Chi-squared test [134 variables]
4. Continuous variables [109 variables]a. Linear regression [29 variables]
5. Selected non-economic variables [54 variables]
Using the selected non-economic variables, the economic variable, and the demographic
factors, multiple logistic regression was employed. Insignificant variables were eliminateduntil all variables were significant.
4.

Results

Table 2. Results of multiple logistic regression
termestimate
std.error
statistic
p.value
0.6819933(Intercept)
4.7476415
3 6.9614193
3.37E-120.2118710
factor(jobindp)2-1.5133172
3 -7.142634
9.16E-13
factor(jobindp)3-2.0988062 0.2397346 -8.7547072
2.05E-18
factor(fightforcountry)
0.2848247 2.4619773 0.0138173
10.7012321
6
1
40.5412021 0.1899225
factor(rceremonies)13
3 2.8495942 0.0043775
0.0419486
CONTROL
0.1658165
8 3.9528417
7.72E-05
0.0852950
0.0007815
Ssecurity-0.2865268
2 -3.3592444
60.0374589
0.0002834
HARDWORK-0.1359758
9 -3.6299913
30.1011319
CONCOURT-0.4184168
4 -4.1373362
3.51E-05
0.1460163
0.0057262
DEMOPOLI-0.4034519
9 -2.7630587
50.0843580
0.0002697
EDUWRY-0.3072919
1 -3.6427111
80.1259824
dclass-0.6010312
1 -4.7707547
1.84E-06
Null deviance: 1194.10 on 918 degrees of freedom
Residual deviance: 785.45 on 907 degrees of freedom
AIC: 809.45

***
***
***
*
**
***
***
***
***
**
***
***

BIC: 867.3312
Number of Fisher Scoring iterations: 5
Number of observations: 919
Pseudo R2: 0.34
*Significant at 0.05%; **Significant at 0.01%, ***Significant at 0.001%
Table 3. Significant variables – question, response coding, and interpretation
Variable
Question
Response
Interpretation
jobindp
V48. Having a job is theAgree [1]People who disagree orbest way for a woman to
Neither [2]choose neither decrease
be an independent person. Disagree [3]the log odds of having
protectionist views by 1.51 and -2.10
fightforcountry* V66. Of course, we all
Yes [1]
People who were willing
hope that there will not be No [0]to fight for their country
another war, but if it wereincrease the log odds of
to come to that, would
having protectionist
youviews by 0.70
be willing to fight foryour country?
rceremonies
V150. With which one of To follow
People who believed
the following statements
religious norms religion was about
do you agree most? The
and ceremonies following norms andbasic meaning of religion [1]ceremonies increased theis:log odds of having
To do good toprotectionist views byother people [0] 0.54
CONTROL
Some people feel they
No choice at all People who feel that they
have completely free[1]
have greater choice andchoice and control overcontrol in what happens
their lives, while other
A great deal of to them increased the log
people feel that what they choice [10]odds of having
do has no real effect onprotectionist views bywhat happens to them.
0.17
Please use this scale
where 1 means "no choiceat all" and 10 means "agreat deal of choice" toindicate how much
freedom of choice andcontrol you feel you haveover the way your life
turns out
Ssecurity
V72. Living in secure
Very much like People for whom securesurroundings is important me [1]surroundings were lessto this person; to avoid
Like me [2]important had lessanything that might beSomewhat like protectionist views by dangerous.
me [3]
0.29

HARDWORK

V100.

CONCOURT

Could you tell me howmuch confidence you
have in them:
V114. The courts

DEMOPOLI

For each one, would you
say it is a very good,
fairly good, fairly bad orvery bad way of
governing this country?
V130. Having a
democratic politicalsystemTo what degree are you
worried about thefollowing situations?
V182. Not being able togive my children a goodeducationEDUWRYdclass*V238. People sometimes
describe themselves as
belonging to the working
class, the middle class, orthe upper or lower class.
Would you describe
yourself as belonging tothe:*Also significant in Mayda’s (2006) model.
5.

Discussion

A little like me[4]
Not like me [5]Not at all likeme [6]In the long run,
hard work
usually brings a
better life [1]Hard work
doesn’tgenerally bringsuccess - it's
more a matterof luck andconnections[10]
A great deal [1]Quite a lot [2]Not very much
[3]
None at all [4]Very good [1]Fairly good [2]Fairly bad [3]Very bad [4]Very much [1]A good deal [2]Not much [3]Not at all [4]Upper class [1]Upper middle
class [2]Lower middle
class [3]Working class[4]
Lower class [5]People who did not
believe hard work
brought successdecreased their log oddsof having protectionist
views by -0.14

People who had lessconfidence in the courts
decreased the log odds of
having protectionist
views by -0.42
People who believed ademocratic politicalsystem was a bad systemdecreased the log odds of
having protectionist
views by -.40

People who were lessworried about providing
a good edu for theirchildren decreased thelog odds of having
protectionist views by 0.31
People who were lower
class decreased the log
odds of having
protectionist views

Overall, the model shows significant improvement from previous research in terms offit. When Mayda’s model is applied only to Thailand, the model has a pseudo r-squared ofabout 20.6 percent. The r-squared for this model shows a 13.6 percentage point increase in
the fit of the model, at 34.2 percent. This finding shows that the methodology used to find thedeterminants of protectionist views of the labor market is robust and an improvement on
previous methods using social survey data.
In contrast to previous models, the economic variable (highest education attained)
was not found to be significant. While multi-country studies generally find that higher
education attainment is correlated with more inclusive views towards immigrants, this trend
does not remain true when applied to just Thailand. This finding reveals one of the problems
with multi-country studies, which is that they can obscure differences between countries. In
their review of cross-national studies of attitudes towards immigrants, Ceobanu andEscandell describe the inverse relationship between education and more inclusive attitudes
towards immigrants as “a remarkably consistent finding” (Ceobanu and Escandell, 2010, pp.
319). However, these studies covered only developed countries and almost exclusively
Western countries (Japan and Korea were included in some studies). Mayda’s study, which
included more developing countries, had a relatively low r-squared overall, at 6%. When she
limited the study to only the developed countries included in the International Social Survey
Programme (ISSP), this r-square increased substantially to 20%. These findings as well as thefinding that education was not significant in the case of Thailand support the theory that
education may be more influential in Western, developed countries but not in others. Whileprevious research has found that education is very significant in determining attitudes, thisdoes not appear to be the case in Thailand, suggesting that an overrepresentation of Western,developed country had led to an overemphasis on education in determining people’s attitudes.
Though highest education was not found to be significant, subjective social class wasfound to have a significant relationship with protectionist views. People who identify aslower social classes are less likely to have protectionist views. Social class differs from theeconomic variable of highest education attained, as it encompasses both economic standing
and social determinations, like prestige and status. Interestingly, this finding contradicts
previous research which finds that people who are in competition with immigrants – in thecase of Thailand, these are individuals with lower skill levels and lower economic standing –should have less favorable attitudes towards immigrants. The data here shows the opposite istrue in Thailand. Rather, those with economic situations more similar to that of migrants
appear to have less protectionist views towards immigrants in the labor market. This finding
suggests that current conceptions of realistic group conflict with respect to immigrants andnatives in the labor market may be limited in their scope, or that other, more salient groupconflicts may be at play.
The significant non-economic variables can be broadly organized into four major
determinants of people’s attitudes towards immigrants, based on which sociological or
economic theory aids in their interpretation. The first is group identification and perceived
threat, both economic and social. This determinant means that people who more strongly
identify as part of a group will have more negative attitudes towards people outside of thisgroup. Likewise, people who feel more threatened or insecure in their livelihood will more
intensely identify with their ingroup to the detriment of the outgroup. While this determinant
could be considered two separate determinants, they are combined here because of thisrelationship. Importantly, this phenomenon occurs because of the perception of threat and cantherefore vary amongst individuals even within the same socioeconomic class.
People who showed greater national pride, i.e. those who were willing to fight for
their country if there was a war, showed more protectionist views, which is consistent with
Mayda’s findings. Individuals who were more worried about providing their children with agood education were found to have more protectionist views, consistent with the theory thatfeelings of threat and insecurity intensify out-group rejection. Furthermore, respondents who
put a greater value on security were also more likely to have protectionist views. Thesefindings suggest that feelings of threat, insecurity, and aversion to risk do indeed lead togreater rejection of outgroup members and a prioritization of ingroup members.
The second determinant is institutional confidence. Overall, those with lessinstitutional confidence are found to have less protectionist views. This finding is especially
important because it is specific to Thailand’s unique history and political system. It is easy to
imagine that in another country, less institutional trust could be related to more protectionist
views. Those with less confidence in the courts were found to have less protectionist views.
Respondents who felt that a democratic political system was a bad way of governing thecountry were also less likely to have protectionist views.
In order to understand this result, it is important to keep in mind several key facts.
First, the data shows a large skew, with 93.8 percent of respondents stating that a democratic
political system is a very good or fairly good way to govern the country. Secondly, Thailand
is a constitutional monarchy with a parliamentary system. However, the Kingdom’s
democracy is turbulent, having experienced 12 successful coups since the implementation of
the first constitution in 1932. Civil liberties are at times curtailed, often falling short of whatsome consider essential to democracies, such as freedom of the press, the existence of very
strict lèse-majesté laws and tightly controlled elections. A democratic system has historically
been tied to other imperatives and political institutions, such as development, modernization,and the monarchy itself. Therefore, the meaning of democracy within Thailand is unique toits political history and more contested than in other countries. Finally, the timing of thissurvey is incredibly important as it was conducted in 2012, only a year before Thailand’s
most recent coup and the installment of the military junta. Thus, a precise definition of what
respondents consider democracy is nearly impossible to manage. With the available data andunderstanding that definitions of democracy may vary widely amongst respondents,
individuals who felt that democracy was a bad way of governing the country are rejecting thenormative political system promoted by the state. Thus, less confidence in a democratic
political system signals a greater lack of trust in the institutions upheld at least nominally by
the government. Both of these variables show the same trend, namely that less trust in
institutions was correlated with more inclusive attitudes towards immigrants.
This finding shows a stark difference with the research conducted in Europe. In across-national study of European countries, higher institutional trust was found to becorrelated with more inclusive attitudes towards immigrants (Halapuu et al., 2013). A similar,
single country study found the same trend in England (Andreescu, 2011). This finding
highlights how determinants of attitudes towards immigrants are heavily context and country
dependent. While one trend may hold true in the countries most commonly studied, further
investigation in a country with a very different political and social context show how thispattern can be easily reversed.
The third group of variables found in the model relates to agency. People who
expressed the view that people have a large amount of control over their futures were more
likely to have protectionist views. Variables related to hard work and agency can be grouped
together into this third determinant. Respondents who felt that success in life was more a
product of luck and connections rather than their own efforts were less likely to haveprotectionist views towards immigrants in the labor market. Similarly, respondents who felt
less choice and control in how their lives turned out also had less protectionist views towards
immigrants. This finding is reinforced by the fact that both variables trend in the same
direction, with feelings of less control relating to less protectionist views.

Finally, the final variable, following norms, is less clear and more difficult tointerpret. Respondents who felt that religion’s main purpose was to follow norms andceremonies rather than to do good to other people were more likely to have protectionist
views. In this case, the question is clear that the importance of following norms for their sakerather than for their effects has a clear relationship with attitudes towards immigrants.
Respondents who disagreed that a job was the best way for women to become independent
were more likely to have protectionist views. This question is difficult to interpret precisely
as the respondents’ attitudes towards female independence, the value of independence itself,
and what avenues besides labor are better for female independence, are not revealed throughthis question. However, Kuasirikun describes Thai culture as “fundamentally patriarchal”(Kuasirikun, 2011, pp. 57); traditional roles for women are subordinate to men andcircumscribed by the household and private sphere. 3 As such, women’s labor is traditionallyconfigured as remaining within the household (Coyle & Kwong, 2000), and the view thatwomen should work outside the home is contrary to traditional norms. Thus, these twoquestions can be categorized as subscription to traditional, normative views. Both find apositive relationship between traditional views and protectionist views against immigrants.
6.
Conclusion
In conclusion, this model for the determinants of attitudes towards immigrants in
Thailand found four overarching categories: group identification and perceived threat,
institutional confidence, agency, and adherence to traditional norms. Results for questions
related to perceived threat and outgroup rejection remained consistent with current theories,
showing an positive relationship between greater identification and greater perceived threatwith more protectionist views. Institutional confidence had an inverse relationship withprotectionist views, a pattern determined by Thailand’s unique political history and contrary
to previous findings. Feelings of greater agency and greater adherence to traditional values
were also positively related with protectionist views.
This model represents an improvement upon previous models in terms of fit.
Furthermore, it highlights some of the shortcomings in multi-country studies which use thesame set of variables for varied cultures and which cover almost exclusively Western
societies. Educational attainment, usually a highly determinant factor, was not found to besignificant. Rather, social class was found to be significant and showed that people who
identified as lower classes were more likely to have inclusive views towards immigrants.
This finding implies that intergroup conflict theories when applied to immigration andintegration may need to consider the wider context and salience of intergroup conflicts in the
country.
In order to fully understand the findings of this study, future research will expand toinclude more countries and perform community analysis of the determinants of attitudes
towards immigrants for each country. Such an analysis will allow the differences between
3

The role of women in the private and public sphere has not been static in Thailand and is influenced by various
factors. First, the value of women’s labor and their role outside of the household depends in part on the
woman’s socio-economic status and other compounding factors. Industrialization and increased migration fromthe country to the city have changed the division of labor between men and women has also changed
dramatically in Thai society, with women often losing ground in the public sphere as work and the homebecame more separated (Buranajaroenkij, 2017). Traditional institutions in Thai society also have an influenceon the gender roles for women. In Thai Buddhism, women are not able to become monks and must acquire
merit “vicariously” through their sons becoming monks. Women are often portrayed as “‘contaminants’ and‘temptresses’ standing in the way of men's deliverance from materialism” (Coyle & Kwong, 2000, pp. 496).
Finally, the Thai government during modernization after World War II propagating the image of the ideal Thai
woman as “who maintains the values and traditions of the family and the country and fulfills the role of thegood mother and wife” (Buranajaroenkij, 2017, pp. 3), which primarily confined women to the household.

countries to become more clear and represent a significant improvement on models whichcurrently assume a more isomorphic cultural and political context. Finally, future researchaims to present a full comparison amongst countries, answering questions such as under what
conditions is education an important determining factor, when is institutional trust positively
correlated with protectionist attitudes towards immigrants and when is it correlated withinclusive attitudes, and whether non-economic factors like agency, tradition, and women’slabor show a similar effect across countries.
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