Does economic self-interest determine public attitudes
toward immigrants? An econometric case study inJapan
Shingo Takahashi
Ana Maria Takahashi
January 2022
Discussion Paper No. 2201

GRADUATE SCHOOL OF ECONOMICS
KOBE UNIVERSITYROKKO, KOBE, JAPANDoes economic self-interest determine public attitudes
toward immigrants? An econometric case study inJapan.
Shingo Takahashi
Hiroshima University, Graduate School of Humanities and Social Sciences
1-5-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8529, Japan
E-mail: staka29@hiroshima-u.ac.jp
Ana Maria Takahashi
Kyoto University of Foreign Studies, Department of Global Studies
6 Kasame-cho, Saiin, Ukyo-ku, Kyoto, 615-8558, Japanand Kobe University, Graduate School of Economics, Japan
E-mail: a takaha@kufs.ac.jp
Abstract:
We examine two economic self-interest hypotheses of the determinants of public attitudes
towards immigrants: (1) labor market hypothesis, which states that the employment andwage impacts of immigration determine public attitudes and (2) the welfare state hypothesis, which states that natives negatively perceive immigrants for fear of straining thecountry’s welfare budget. The first hypothesis predicts that natives’ education will affect pro-immigrant attitudes more positively when the immigrants are from lower-income
countries. The second hypothesis predicts that natives’ income will aﬀect the pro-immigrant
attitudes more negatively when the immigrants are from lower-income countries. We use
the Japanese General Social Survey, which asks respondents’ tolerance toward immigrants
from diﬀerent countries, allowing us to remove the unobserved individual characteristics ina fixed eﬀect estimation. Our results show no diﬀerence in education and income eﬀects
on pro-immigrant attitudes regardless of whether immigrants are from high- or low-income
countries. We conclude that economic self-interests do not explain Japanese public attitudes
towards immigrants. We discuss policy implications on how to improve public attitudes towards immigrants.

1.

Introduction

The labor economic theory predicts that the employment and wages of native workers decrease when immigrants with substitutable skills flow in and increase when immigrants withcomplementary skills flow in. This indicates that the high-skilled natives might perceivehigh-skilled immigrants as a threat and thus view them negatively, but positively perceive
low-skilled immigrants who are likely to be their complements. This is “the labor market
hypothesis” of the determination of the natives’ attitude towards immigrants.
1

Another economic channel through which natives’ attitude is shaped is the anxiety
that immigrants might strain the country’s welfare budget. While studies such as Preston(2014) and Dustmann and Fratini (2014) found that the overall fiscal eﬀects of immigrants
are positive, immigrants abusing social welfare is a common narrative against immigrants.
Regardless of whether such anxiety is warranted, if such a concern shapes perception towards immigrants, high-income natives would negatively perceive low-skilled immigrants
since high income natives would pay a greater share of welfare budget due to the progressive personal tax, and low-skilled immigrants may be at risk of receiving social security
benefits. The same argument also indicates that high-income natives may welcome highskilled immigrants, since they are likely to contribute to the welfare budget, relieving theirtax burden. This is the welfare state hypothesis of the determination of natives’ attitudes
towards immigrants.
These two hypotheses constitute the economic self-interest hypotheses of the determinants of natives’ attitudes towards immigrants. The labor market hypothesis was firsttested by Scheve and Slaughter (2001), who used education as a proxy for skills. They foundthat in the US low-skilled natives are more likely to oppose immigration. Using data fromseveral European countries, Mayda (2006) found that in countries where natives are moreeducated than the immigrants, a strong positive correlation exists between the natives’ skills
and support for immigration.1 The welfare state hypothesis was first tested by Hanson etal. (2007), who found that richer natives are more likely to oppose immigration, supporting
the welfare state hypothesis. Facchini and Mayda (2009) also found that natives’ income isnegatively correlated with pro-immigrant attitude when immigrants are unskilled.
One problem with using natives’ education or income to test these hypotheses is thatthey are likely to be correlated with natives’ unobserved characteristics. As d’Homber and1

O’Rourke and Sinnott (2006) used an International Labor Organization’s skill classification and showthat skilled workers are less likely to oppose immigration than unskilled workers.

2

Nunziata (2016) showed, education is likely to be positively correlated with one’s preference
towards cultural diversity. This endogeneity is likely to introduce a positive bias in estimatedeﬀects of education on natives’ pro-immigrant attitudes. In contrast, a person’s income islikely to be correlated with his or her political conservatism, which is likely to introduce anegative bias in the estimated eﬀects of income on the native’s pro-immigrant attitudes.
As such, subsequent development of the literature finds mixed evidence for the labor market hypothesis. Hainnmuller and Hiscox (2007 and 2010) found education to becorrelated with a positive attitude toward both low- and high-skilled immigrants, contradicting the economic self-interest hypothesis. Biavaschi et al. (2018) used South African
data where immigrants are more skilled than natives, and yet found that education to bepositively correlated with pro-immigration attitudes, which is inconsistent with the labormarket hypothesis. Facchini and Mayda (2012), however, showed that education is negatively correlated with natives’ support for skilled immigrants, supporting the labor market
hypothesis. The support for the welfare state hypothesis, in contrast, has been more consistent. For example, Dustman and Preston (2007) found that welfare state concern is themost dominant determinant of natives’ attitude toward immigrants, with a similar result
found by Boeri (2010).2
The goal of this study is, thus, to re-examine the two economic self-interest hypotheses
while accounting for the aforementioned endogeneity problems. The dataset we use is theJapanese General Social Survey (JGSS). The 2008 JGSS asks information regarding natives’perceptions of immigrants from diﬀerent countries or regions: China, South Korea, Taiwan,
South East Asia, Europe, and North America. The labor market hypothesis predicts that
education will have greater eﬀects on the native’s pro-immigrant attitudes if immigrants
2

Fauvelle-Aymar (2014) found that educated natives are less favorable to migrants when they can potentially influence the welfare policy, that is, when they have the right to vote. In this study, education isused as a proxy for income.

3were from low-income countries (that are likely to send low-skilled immigrants) than ifthey were from high-income countries (that are likely to send high-skilled immigrants).
As the JGSS asks about the same individual’s attitude towards immigrants from diﬀerent
countries, we can eliminate the unobserved characteristics using a method akin to the fixedeﬀect estimation. The same method can be applied to test the welfare state hypothesis,
where our focal relationship is between natives’ income and their pro-immigrant attitude.
We believe that this study is one of the first in the related literature to explicitly deal withendogeneity arising from individual level fixed eﬀects.
Studying Japanese case is interesting because there have been no academic studies on
economic self-interest hypotheses in Japan. Japan has been a reluctant accepter of unskilled migrant workers despite the fact that it faced shortage of such workers time to time,
including the current time. Japan’s immigration law, the Immigration Control Act (ICA),
was enacted in 1951, but until the most recent modification of this law in 2018, Japan
had no work visa categories for unskilled workers. Unskilled migrant workers had been
accepted through a back-door channel called a trainee system. This reluctance to admit
unskilled workers is undoubtedly influenced by citizen’s presumed negative attitudes toward
low-skilled immigrant workers.3 By understanding how the natives’ attitudes towards immigrants are formed, the government can formulate a better policy to improve the citizens’
attitudes towards immigrants.
The rest of the paper is organized as follows. Section 2 provides an overview of theJapanese immigration policies regarding low-skilled immigrants. Section 3 presents our
econometric method and data. Section 4 presents our estimation results, while Section 5
concludes this paper with a discussion.
3

See Facchini and Mayda (2008) for the evidence that public attitudes towards immigrants shape theimmigration policies.

4

2.

An overview of immigration policies regarding unskilled migrant workers in Japan

Japan’s immigration law, ICA, was geared towards skilled immigrants and provided no legal
channels for unskilled migrant workers to enter Japan for paid jobs until its most recent
revision in 2018.4 This policy of prohibiting the inflow of unskilled foreign labor became
diﬃcult to sustain when Japan experienced its first wave of labor shortage in the 1980s,
particularly in the construction industry, following rapid economic growth.
This labor shortage was initially met by employing illegal migrant workers. These
workers “initially enter Japan legally using tourists, student, or other types of nonworking
visas (Spencer 1992, p764).” The number of immigrant workers apprehended for ICA
violation increased from 6,830 in 1984 to 22,626 in 1989, an increase of 230% (Spencer1992). The first major revision of the ICA was done in 1989 with this background. This
revision was a compromise between the Japanese immigration policy’s guiding principle of
not admitting unskilled migrant workers and the reality of labor shortage for low-skilledworkers. The 1989 revision established a “trainee system” where unskilled migrant workers
can stay in Japan for one year in order to aquire skills through on-the-job training andthen take the skills back to their countries. As the oﬃcial purpose was skill transfer (fromJapan to developing countries), the accepting companies were required to provide non-worktraining, such as Japanese language training, for at least one-third of the training periodwith strict limitation on the number of trainees a company can accept.5
The short duration and rigid requirements of the trainee system made it diﬃcult for
the accepting companies to recover the training costs, causing the accepting companies’s
4

There was a visa category for “persons who do not fall under any other status but are permitted toreside at the discretion of the Minister of Justice”. However, given the Japanese government’s stance against
allowing unskilled foreign laborers, Spencer (1992) noted that the Japanese government steered away fromthis option of allowing unskilled migrant workers.
5
For a company with 20 workers or less, the number of trainees was limited to three.

5dissatisfaction to grow. In this background, the ICA was revised again in 1993, establishingthe “technical intern training” system. Under this system, an immigrant completing theinitial one-year of trainee program can apply to become a “technical intern trainee”. Onceaccepted as a technical intern trainee, the immigrant can extend the stay for two more
years.
A major diﬀerence between a trainee and a technical intern trainee was that, the latter
was legally treated as a worker who could earn wages. The former was not legally a worker,
and therefore, could not work for wages. Trainees were paid the “living expense allowance”
instead of wages. However, the diﬀerence between wages and living expense allowance
was not necessarily large. According to Nishioka (2004), the average after-tax wages for atechnical intern trainee was about 100,000 yen, while the average living expense allowance,
which was not taxed, was 83,000. Another diﬀerence was that companies were not allowed
to let trainees work overtime, but there was no such restriction for technical intern trainees.6
As mentioned earlier, the oﬃcial purpose of the trainee and technical intern trainee
systems was to provide the immigrants opportunities to acquire valuable skills from Japan,
and then transfer the skills back to their own countries. This system undoubtedly fosteredsuch skill transfers. However, the trainee and technical intern trainee systems were alsosystems through which Japanese companies could hire temporary unskilled migrant workers.
In 2010, 32% of foreign workers in Japan (including trainees and technical intern trainees)
were trainees.7 Insisting on the oﬃcial purpose of skill transfers when these trainees were
6

In terms of visa status, trainees and technical intern trainees were placed in the “Designated Activities”
category. Designated Activities was the category for miscellaneous visas such as working holiday visa. This,
however, changed in 2010, when the ICA was revised to create the “technical intern trainee” as a separate
category, and the previous technical intern trainee system under designated activities was abolished. This
allowed accepting companies to skip the ‘trainee’ period, and directly hire migrant workers as proper wageearning workers, albeit still as trainees. The maximum duration that an intern can stay in Japan was three
years.
7
Based on Zairyu Gaikokujin Toukei (Foreign Residents Statistics) published by Immigration Service
Agency of Japan. We include in foreign workers the following visa categories: (1) professors, (2) artists,(3) Religious activities, (4) Journalists, (5) business managers, (6) Legal/Accounting services, (7) Medical
services, (8) Researcher, (9) Instructor, (10) Engineer/Specialists in humanities/international services, (11)Intra-company transferee, (12) Nursing care, (13) Entertainer, (14) Skilled labor, (15) trainees/technical6

actually unskilled migrant workers caused problems. By insisting on the oﬃcial purpose, thegovernment had to ensure that the skill acquisition be conducted according to a consistentplan under the same employer. Thus, the trainees (including technical intern trainees) were
not allowed to change their employers, and this often lead to abusive work environments(Suuchi 2019). As for employers, the procedure to accept trainees was onerous (Kamibayashi2009), and the restriction on number of workers meant that they could not employ a desired
number of trainees (Kamibayashi 2019).
The second wave of shortage for unskilled workers in Japan resulted from aging of the
population and low inflow of immigrants. In 2010, Japan’s fertility rate was 1.3, one of
the lowest among OECD countries. Japan’s share of foreign born population in the total
population was 1.8%, which is again one of the lowest in the OECD countries.8 Given thisbackground the ICA was revised in 2018 to create a new category of work visa for unskilledworkers, called Specific Skill Visas (Tokutei Ginou Visa). This visa is restricted to 14
industries such as care workers, building cleaning, and agriculture.9 The initial durationof the visa is five years, and if the worker passes a skill test during this period, the visa
can be extended up to another five years. For the initial period of five years, workers
are not allowed to bring their families, but for the next five years, they can bring theirfamilies. This visa is available only to migrants from nine countries: Vietnam, Philippines,
Cambodia, China, Indonesia, Thailand, Myanmar, Nepal, and Mongolia. There is also a
cap for the number of accepting workers: 345,000 (Kamibayashi 2019).
intern trainees. The percentage is based on the authors computation.
8
This compares to 6.9% of the US, 9.29 of the UK, and 7% of the OECD average.
9
The full list includes care workers; building cleaning; machine parts and tooling industry; industrial
machinery; electric, electronics and information industry; construction industry; automobile repair andmaintenance; aviation industry; accommodation industry; agriculture; fishery and aquaculture; manufacture of food and beverages; and food industry.

7

3.

Empirical method and data

We use the 2008 wave of the JGSS. The JGSS is the Japanese counterpart of the GeneralSocial Survey in the US and Europe for international comparisons. The sample is representative of men and women aged 20 to 89 in Japan. Although the JGSS is now available up
to the 2012 wave in the University of Michigan’s data sharing site ICPSR, we use only the2008 wave of the data for the reason described below.10
In the 2008 wave of the data, the measure of respondents’ attitudes toward immigration
is based on the answer to the following question:
Question: How would you feel about having neighbors who are from the following countries or regions? Can you accept the people who are from each of the following countries orregions?
The countries and regions listed in the question are China, South Korea, Taiwan, South
East Asia, Europe, and North America (US and Canada). For each country or region,
respondents answer either: “yes” or “no”. Thus, this question elicits the attitudes of a
respondent toward immigrants from diﬀerent countries, allowing us to eliminate individuallevel unobservables using a method akin to fixed-eﬀects estimation. Unfortunately, the 2008
wave is the only one that asks this question, and therefore our data is restricted to thiswave.11
Now, let us explain our method. Based on the survey question mentioned above, let
T olerancec,i be a dummy equal to 1 when the respondent i says “yes” to immigrants fromcountry or region c. Then, consider the following linear probability regression,
T olerancec,i = βc,0 + δc Educationi + γc Incomei + βc′ Zi + ai + uc,i10

(1)

Waves that are available in English in are, 2000, 2001, 2002, 2003, 2005, 2006, 2008, 2010, and 2012.
We mention, however, that in all the data waves, the following question is asked: ‘Are you for oragainst an increase in the number of foreigners in your community?’ Respondents answer either “for” or“against”. Unfortunately, this question does not require respondents to report their attitude by the countryof origin of the immigrants.
118

where Zi is the vector of variables that are expected to directly aﬀect T olerancec,i , coefficients δc and γc show the eﬀects of natives’ education and income on tolerance toward
immigrants from country or region c, uc,i is the usual error term uncorrelated with anyof the explanatory variables, and ai is individual respondent’s unobserved characteristics
such as one’s cultural openness or political conservatism. As cultural openness is likely
to be positively correlated with the respondent’s education level, an ordinary least square(OLS) estimate of δc is likely to be positively biased. Political conservatism is likely to bepositively correlated with one’s income, with a possible negative eﬀect on tolerance. This
may negatively bias the OLS estimate of γc . Having said so, income can also be correlatedwith an array of other factors. For example, higher income might allow one to live in cosmopolitan areas, resulting in a more liberal views toward immigrants. Thus, the directionof the bias for γc is not certain.
Now, let us explain how we test the labor market hypothesis while taking into accountthe endogeneity stemming from the unobservables. The (unbiased) value of δc depends
on the skill mix of immigrants from country c. If all the immigrants from country c are
non-skilled workers, we expect δc to be positive because non-skilled immigrants are thecomplement for high-skilled natives. Similarly, if all the immigrants from country c areskilled-workers, we expect δc to be negative since skilled immigrants are the substitute forthe skilled natives.
In reality, each country sends both skilled and unskilled workers. If the labor market hypothesis holds, as the skill mix of immigrants tilts toward unskilled workers, δc will
increase because more of the immigrants are substitutes of educated natives. This implication can be tested. Suppose that there are two countries, one low-income and the otherhigh-income. Then, δL > δH , where L denotes a low-income country, and H denotes a highincome country. We then use the following notation: ∆T oleranceL−H,i = T oleranceL,i 9

T oleranceH,i . Now, we have;∆T oleranceL−H,i = (βL,0 − βH,0 ) + (δL − δH )Educationi(2)+ (γL − γH )Incomei + (βL − βH )′ Zi + (uL,i − uH,i )This equation eliminates the bias stemming from the presence of unobserved characteristics.
If the attitude toward immigrants is determined according to economic self-interest, thenthe coeﬃcient for education should be positive, that is δL - δH >0. This is our test of thelabor market hypothesis.
The same logic applies to testing of welfare state hypothesis. Richer natives would
perceive immigrants from poorer countries more negatively than they would perceive immigrants from richer countries, because immigrants from poor countries are perhaps more
likely to be the beneficiaries of the welfare system. This indicates that δL < δH . Thus, if thewelfare state hypothesis is correct, we expect δL - δH <0. We classify Taiwan, Korea, North
American, and Europe under high-income countries and regions while China and South
East Asia under low-income countries and regions.12
The variables and their summary statistics are listed in Table 1. We control for theindividual characteristics that would aﬀect one’s attitude toward immigrants. Our focal
explanatory variables are the years of education and the respondent’s family income. We
include a dummy for unemployed workers since being unemployed might make one feel
more vulnerable to an increased competition. In contrast, those who are not seeking jobs
might be indiﬀerent about an increased competition, and thus we include a dummy forhome makers.
We control for one’s stated political orientation, conservative or progressive, with nei12

As of 2008, Japan’s GDP per capita was US$39,393. Taiwan’s GDP per capita (USD$18,081) wasmuch lower than that of Japan, though it was nearly 6 times higher than that of China’s US$3,394, and12 times higher than the South East Asian’s average US$1,445. Korea’s GDP per capita as of 2008 wasslightly higher than that of Taiwan’s US$21,294. North American average was USD$47,53), and European
Union average was US$38,572. All the data are derived from OECD statistics except for the EU statistic,
which was derived from the eurostat (https://ec.europa.eu/eurostat/en/).

10

ther conservative nor progressive as the base category. Interactions with foreigners reduces
prejudices (Pettigrew and Tropp, 2006), and therefore we include whether one interact
sometime or frequently with foreigners. The base category is those who seldom or neverencounter foreigners. Similarly, we include dummies for whether one has studied abroad,and whether one has visited one of our focal countries of regions. We also include dummies
for whether one has acquaintances from one of our focal countries or regions. We included adummy for whether one has experienced robbery (by force or threat) or burglary this year,
as increasing crimes is another common narrative against immigrants. We control for sizeof the cities within Japan by including dummies for (1) large cities, (2) medium cities, (3)small cities, and (4) towns and villages.13 .
After eliminating observations with missing variables, we have 1,996 observations. The
average tolerance varies with the immigrants’ countries or regions of origins. In an ascendingorder, 63.5 percent of respondents said that they will accept neighbors from China, 67.1
percent in case of South East Asia, 68.7 percent in case of Korea, 70.8 percent in the caseof Taiwan, 74.6 in the case of Europe and 75.2 in the case of North America. Thus, thetolerance is generally higher for immigrants from wealthier regions.
The respondents’ average education is 12.7 years, and average age is 52 years. While
Japan is known to be an insular country, a fair share of respondents interact with foreigners
frequently (13%) or sometimes (34.5%). A substantial share of respondents has visited our
focal countries or regions; this ranges from 12.5% visiting Taiwan to 24% visiting North
America. Not a negligible share of respondents have acquaintances in these countries andregions, ranging from 4% in Taiwan to 9% in North America.
13

The large cities are Sapporo, Sendai, Saitama, Chiba, Tokyo Metropolitan Area, Yokohama, Kawasaki,
Niigata, Shizuoka, Hamamatsu, Nagoya, Kyoto, Osaka, Sakai, Kobe, Hiroshima, Kitakyushu, and Fukuoka.
Medium-sized cities are those with a population of 200,000 or more. Small cities are those with population
less than 200,000. Towns and villages are smaller than small cities and are the base category.

11

4.

Empirical results

Before showing our main results obtained using the pair-wise diﬀerence in attitude, we
present our results obtained from a simpler model using tolerance toward immigrants froma particular country or region, T olerancec,i , as the dependent variable. Table 2 presents
the results. The coeﬃcients for education are positive and statistically significant for all
the countries and regions, ranging from 0.2 to 0.22. As explained earlier, these coeﬃcientsare likely to be biased upward due to the presence of unobserved factors, such as cultural
openness.
Household income has a small and statistically insignificant coeﬃcients for all the Asian
countries and regions. However, it has positive and marginally significant coeﬃcient for
Europe and North America. A positive coeﬃcient for wealthy regions is consistent withthe welfare state hypothesis, although we expect these parameters to be biased due to thepresence of unobserved respondent characteristics.
Interactions with foreigners are positively correlated with the tolerance toward immigrants, although this correlation is only in “some interactions”. Frequent interactions
are not associated with positive attitudes toward immigrants. The reason could be thatthey represent diﬀerent types of interactions. For example, “some interactions” might predominantly represent the natives’ interactions with foreign language instructors, which isdesigned to provide a positive experience. “Frequent interactions” might represent moremundane interactions such as interactions at work or with shop keepers.
Having acquaintances from low-income countries is generally associated with a higher
tolerance toward immigrants from all countries and regions. This association is not evident
in the case of richer countries. This pattern might indicate that personally knowing foreigners from low-income countries removes the negative prejudice associated with immigrants

12

from such countries, leading to more liberal views toward immigration. It may also be thatthose with liberal attitude are more willing to travel to less wealthy countries or regions.
Now, we present our main results based on Equation (2), which uses a country-pair
diﬀerence in tolerance as the dependent variable. Table 3 shows the results. As we have
two low-income countries/regions and three high-income countries/regions, we have eight
low-high pairs. Among them, we are particularly interested in the China-Taiwan pair, whichis shown in Model 1. Immigrants speaking Chinese have an advantage in Japanese language
acquisition as compared to those speaking other native languages because Japanese language
makes extensive use of Chinese characters. Thus, even if China’s GDP per capita is much
lower than that of North America or Europe, educated Japanese natives might still consider
Chinese workers to be a greater threat. A comparison of Chinese and Taiwanese immigrants
would hold the language eﬀect constant while allowing for comparing the attitudes towards
low- and high-income immigrants.
Model 1 shows a very small and statistically insignificant coeﬃcient for education,
rejecting the labor market hypothesis. The coeﬃcient for the household income is also
small and statistically insignificant, rejecting the welfare state hypothesis. In fact, thecoeﬃcients for both education and household income are small and insignificant regardlessof whether the comparison is within Asian countries (Model 1 to Model 4) or between
Asian countries and European/North American countries (Model 5 to Model 8). Thus, weconclude that the two economic self-interest hypotheses do not explain the Japanese natives’
attitudes towards immigrants. While many studies rejected the labor market hypothesis,
the rejection of welfare state hypothesis is new to the literature.
Then, why does the economic self-interests not shape the Japanese citizens’ attitudes
towards immigrants? It could be that Japanese residents are acutely concerned about
the labor shortage, and this concern dominates both the labor market and welfare state13

concerns, resulting in no supporting evidence for the two hypotheses.
A more likely explanation, however, is that Japanese citizens are more concerned about
non-economic factors such as the racial composition of their residential areas or cultural
diﬀerences. In fact, one of the changes in the 1989 ICA revision indicates that the Japanese
government understood this possibility. While the 1989 ICA revision allowed low-skilled
immigrants to work in Japan very restrictively through a trainee system, another part of therevision created a new visa category that allowed low-skilled immigrants to work without any
restriction–the Resident Visa. This visa allowed the second- or third-generation Japanese
to work in Japan without restrictions.14 By the end of 1992, there were 150 thousand ofsuch immigrants, and the majority of them were the second- or third- generation Japanesefrom Brazil. Many of them worked as manual workers, for example, in the car and electricparts industries (Kamibayashi 2015, p.99).
Academic debates about public attitudes toward immigrants often center around whether
economic impacts of immigration or perceived cultural impacts of immigration are more important determinants of public attitudes.15 This study does not explicitly examine the cultural aspects of the determinants. However, our rejection of the two economic self-interest
hypotheses seems to implicitly support the arguments that perceived cultural impacts canbe more important determinants of public attitudes towards immigrants.

5.

Discussion and conclusion

Using the attitudinal data of Japanese citizens, we tested two economic self-interest hypotheses on how natives’ attitudes towards immigrants are shaped. First is the labor market
hypothesis where natives perceive immigrants negatively for fear of increased competition
14

The duration is three years, though it can be renewed.
For the eﬀects of non-economic factors on the public attitudes towards immigrants, see Hainmueller andHopkins (2014), Card, Dustmann, and Preston (2005, 2012), Espenshade and Hempstead (1996), Citrin etal. (1997), and McDaniel et al. (2011)15

14

for jobs and a possible downward pressure on wages. The second is the welfare state hypothesis where natives perceive immigrants negatively for fear of immigrants straining thecountry’s welfare budget.
We dealt with the endogeneity of education and income stemming from individual
unobservable characteristics such as one’s cultural openness, by utilizing a method akinto fixed-eﬀects estimation. From our estimation results, the two economic self-interest
hypotheses do not explain the Japanese natives’ attitudes towards immigrants. Thus, it
is more likely that other issues such as culture or race play a larger role in shaping theattitude of Japanese natives’.
How do our results help improve the attitude Japanese natives’ toward immigrants?
Grigorieﬀ et al. (2016) noted that people are consistently misinformed about immigrants,
such as about the share of immigrants and their unemployment and incarceration, andshowed that providing accurate information about immigrants improves the attitude. Igarashi
and Ono (2020) showed that providing information about the beneficial aspects of immigration in economic, cultural, or security areas improves the natives’ attitudes towards immigrants. Our results indicate that disseminating accurate information about the economic
impacts of immigrants, such as accurate estimates of the impacts on wage or employment,
may not help improve public attitudes because economic self-interests are not what drive
public attitudes. It would be more beneficial to disseminate accurate information about
the non-economic aspects of immigrations, such as their language proficiency or the incarceration rate. Showing immigration as an opportunity for cultural enrichment might beanother way to improve public attitudes towards immigrants.

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17

Table 1: Summary Statistics
Variable

Tolerance towards immigrants from:
China
Korea
TaiwanSouth East Asia
EuropeNorth America
Education (in years)
Household income (in 10,000 yen)
Age
FemaleMarried
Unemployed
Housework
Political orientation:
Conservative
Progressive
Experienced being robbed this year
Interact with foreigner frequently
Interact with foreigner sometime
Ever studied aborad
Ever visited:
China
Korea
TaiwanSouth East Asia
EuropeNorth America
Countries other than above
Have acquaintance(s) from:
China
Korea
TaiwanSouth East Asia
EuropeNorth America
Countries other than above
City size:
Large cities
Medium sized cities
Small cities
No of observations

18

Mean

Std Errors

0.635
0.687
0.708
0.672
0.747
0.752
12.744585.71052.009
0.529
0.704
0.018
0.195

(0.482)(0.464)(0.455)(0.470)(0.435)(0.432)(2.332)(331.527)(16.941)(0.499)(0.456)(0.131)(0.396)

0.278
0.221
0.035
0.130
0.345
0.054

(0.448)(0.415)(0.184)(0.336)(0.476)(0.226)

0.143
0.193
0.128
0.185
0.180
0.240
0.221

(0.350)(0.395)(0.334)(0.389)(0.385)(0.427)(0.415)

0.119
0.107
0.042
0.071
0.055
0.090
0.066

(0.324)(0.309)(0.200)(0.256)(0.228)(0.287)(0.248)

0.218
0.238
0.422
1996

(0.413)(0.426)(0.494)

Table 2: Determinants of tolerance towards immigrants from a particular country or aregion: Dep Var=T olerancec,iVariables

China

Korea

TaiwanSouth East
Asia

EuropeNorth
America

Education (in years)

0.020***(0.005)0.002(0.003)0.063(0.044)-0.008*(0.004)0.010(0.025)0.011(0.027)0.004(0.083)-0.043(0.031)

0.021***(0.005)0.002(0.003)0.035(0.040)-0.006(0.004)-0.009(0.023)-0.008(0.024)0.085(0.059)-0.032(0.029)0.018***(0.005)0.001(0.003)0.057(0.041)-0.008**(0.004)0.026(0.023)0.004(0.025)-0.021(0.076)-0.031(0.030)0.022***(0.005)0.002(0.003)0.022(0.041)-0.005(0.004)-0.002(0.024)-0.011(0.026)0.063(0.068)-0.038(0.030)0.026***(0.004)0.006**(0.003)-0.020(0.037)-0.001(0.004)-0.008(0.021)
0.009(0.023)0.089(0.054)-0.015(0.027)0.023***(0.004)0.004*(0.003)-0.006(0.038)-0.003(0.004)-0.003(0.021)
0.006(0.023)0.081(0.055)-0.013(0.027)-0.027(0.025)0.039(0.027)-0.036(0.057)-0.022(0.034)0.043*(0.023)0.017(0.045)-0.005(0.024)0.070***(0.024)-0.128**(0.058)0.010(0.030)0.050**(0.021)-0.002(0.038)-0.010(0.024)0.049*(0.025)-0.090(0.057)-0.039(0.032)0.048**(0.022)-0.010(0.042)-0.025(0.025)0.046*(0.025)-0.127**(0.058)0.020(0.032)0.047**(0.022)-0.025(0.043)-0.013(0.023)0.045**(0.022)-0.113**(0.056)0.002(0.028)0.052***(0.020)-0.039(0.033)-0.008(0.023)0.052**(0.022)-0.125**(0.056)0.041(0.027)0.062***(0.020)-0.058*(0.034)0.014(0.034)0.078***(0.029)0.009(0.036)0.036(0.030)-0.049(0.031)
0.009(0.027)0.001(0.026)-0.006(0.030)0.047*(0.025)0.046(0.032)0.047*(0.026)0.015(0.027)0.017(0.024)0.015(0.023)-0.019(0.033)0.092***(0.026)0.022(0.034)0.038(0.028)-0.016(0.029)0.005(0.025)-0.006(0.025)-0.015(0.032)0.065**(0.027)0.006(0.034)0.067**(0.028)-0.011(0.029)0.009(0.026)0.033(0.025)-0.012(0.029)0.035(0.024)-0.020(0.031)
0.054**(0.024)0.021(0.025)0.037*(0.022)0.049**(0.021)-0.000(0.029)0.035(0.024)-0.012(0.030)0.056**(0.024)0.015(0.024)0.047**(0.022)0.058***(0.021)

Household income/100
age/10age squared/100
FemaleMarried
Unemployed
Housework
Political orientation:
Conservative
Progressive
Experienced being robbed this year
Interact with foreigner frequently
Interact with foreigner sometime
Ever studied aborad
Ever visited:
China
Korea
TaiwanSoutn East Asia
EuropeNorth America
Countries other than above

Inside brackets are robust standard errors. *,**,***= significant at the 10%, 5%, and 1% levels.

19

Table 2 continued.
Variables

China

Korea

TaiwanHave acquaintance(s) from:
China

South East
Asia

EuropeNorth
America

0.132***
0.101***
0.099***
0.079***
0.074***
0.073***(0.031)(0.026)(0.028)(0.030)(0.023)(0.023)
Korea
0.064*
0.031
0.105***
0.049
0.031
0.039
(0.034)(0.030)(0.030)(0.033)(0.028)(0.028)
Taiwan-0.0280.035-0.034
0.037
0.031
0.017
(0.053)(0.040)(0.048)(0.047)(0.036)(0.038)Soutn East Asia
0.113***
0.090***
0.078**
0.100***
0.050*
0.046(0.036)(0.030)(0.033)(0.034)(0.030)(0.030)Europe
0.019
0.021
0.037
0.051
0.049
0.042
(0.045)(0.037)(0.040)(0.041)(0.030)(0.031)
North America
0.004
0.006
0.022
0.017
0.008
0.008
(0.037)(0.033)(0.034)(0.035)(0.029)(0.029)Countries other than above
0.074*
0.106***
0.102***
0.086**
0.096***
0.081***(0.040)(0.030)(0.034)(0.036)(0.027)(0.028)Large cities
0.035
0.019
0.020
0.018
0.044
0.035
(0.040)(0.036)(0.038)(0.037)(0.034)(0.034)
Medium sized cities
0.017-0.020-0.011-0.009-0.013-0.001(0.039)(0.036)(0.037)(0.037)(0.035)(0.035)
Small cities
0.068*
0.030
0.044
0.055
0.043
0.051
(0.036)(0.033)(0.034)(0.034)(0.032)(0.032)
Constant
0.148
0.344***
0.283**
0.315***
0.417***
0.425***(0.127)(0.114)(0.120)(0.121)(0.107)(0.108)
No obs
1,996
1,996
1,996
1,996
1,996
1,996
R-squared
0.078
0.117
0.093
0.107
0.139
0.132
Inside brackets are robust standard errors. *,**,***= significant at the 10%, 5%, and 1% levels.

20

Table 3: Determinants of the diﬀerence in tolerance towards immigrants from low-income
and high-income countries/regions: Dept Var = T oleranceL−H,iModel 1Model 2Model 3Model 4Model 5Model 6

Model 7

Model 8

Variables

China-Taiwan

China-KoreaSE Asia-TaiwanSE Asia
Korea

China
-America

China-Europe

SE Asia-America

SE Asia
EuropeEducation (years)-0.001(0.003)-0.0004(0.002)0.029(0.027)-0.001(0.002)0.020(0.016)0.019(0.017)-0.081(0.065)-0.011(0.019)0.002(0.003)0.0004(0.002)0.007(0.024)0.000(0.002)-0.016(0.015)0.007(0.017)0.025(0.033)-0.012(0.018)0.001(0.003)0.0003(0.002)-0.012(0.022)0.001(0.002)0.008(0.013)-0.003(0.014)-0.021(0.040)-0.007(0.015)0.004(0.003)0.001(0.002)-0.035(0.029)0.003(0.003)-0.028*(0.016)-0.016(0.018)0.084(0.062)-0.007(0.018)-0.002(0.004)-0.003(0.003)0.070**(0.035)-0.005(0.003)0.014(0.020)0.005(0.021)-0.077(0.065)-0.030(0.025)-0.006(0.004)-0.004(0.003)0.083**(0.033)-0.006**(0.003)0.018(0.020)0.002(0.021)-0.085(0.071)-0.027(0.025)-0.000(0.003)-0.002(0.002)0.029(0.028)-0.002(0.003)0.002(0.016)-0.017(0.018)-0.018(0.050)-0.025(0.020)-0.004(0.003)-0.003(0.002)0.042(0.027)-0.004(0.003)0.006(0.016)-0.020(0.017)-0.025(0.049)-0.023(0.020)-0.022(0.016)-0.031*(0.018)0.092***(0.034)-0.031(0.025)-0.007(0.015)0.019(0.037)-0.017(0.015)-0.011(0.016)
0.053**(0.022)0.017(0.020)-0.005(0.014)0.028(0.036)-0.020(0.013)-0.024(0.015)0.001(0.033)0.010(0.018)-0.003(0.012)-0.024(0.026)-0.015(0.016)-0.003(0.018)-0.038(0.035)0.059**(0.024)-0.001(0.016)-0.015(0.033)-0.019(0.020)-0.013(0.022)0.089*(0.046)-0.063**(0.027)-0.019(0.019)0.075*(0.042)-0.013(0.021)-0.007(0.023)0.077(0.050)-0.024(0.028)-0.009(0.019)0.056(0.041)-0.017(0.017)-0.005(0.018)-0.002(0.040)-0.021(0.022)-0.015(0.016)0.032(0.029)-0.012(0.016)0.001(0.018)-0.015(0.045)0.018(0.020)-0.005(0.015)0.014(0.031)0.020(0.023)0.031(0.019)-0.037(0.026)-0.011(0.022)-0.064***(0.023)-0.008(0.018)-0.014(0.017)0.033*(0.019)-0.015(0.018)-0.012(0.024)-0.003(0.019)-0.033(0.020)0.004(0.017)0.007(0.014)-0.009(0.018)0.018(0.015)-0.040*(0.024)0.020(0.017)-0.026(0.018)-0.007(0.016)0.019(0.014)0.004(0.021)-0.027(0.018)-0.016(0.027)0.028(0.020)0.005(0.022)0.004(0.019)0.039**(0.018)0.014(0.028)0.042*(0.024)0.021(0.030)-0.020(0.025)-0.064**(0.026)-0.038*(0.022)-0.057***(0.022)0.026(0.028)0.043*(0.024)0.029(0.031)-0.019(0.027)-0.070**(0.027)-0.028(0.022)-0.048**(0.022)-0.014(0.023)0.030*(0.018)0.017(0.025)0.011(0.023)-0.026(0.023)-0.038*(0.019)-0.025(0.019)-0.003(0.023)0.030*(0.017)0.025(0.025)0.012(0.022)-0.032(0.023)-0.027(0.019)-0.016(0.019)Household income/100
age/10age squared/100
FemaleMarried
Unemployed
Housework
Political orientation:
Conservative
Progressive
Experienced being
robbed this year
Interact with foreigner
frequently
Interact with foreigner
sometime
Ever studied aborad
Ever visited:
China
Korea
TaiwanSouth East Asia
EuropeNorth America
Other countries

Inside brackets are robust standard errors. *,**,***= significant at the 10%, 5%, and 1% levels.

21

Table 3 continued.
Variables

China-Taiwan

China-KoreaSE Asia-TaiwanHave acquaintance(s)China

SE Asia
Korea

China
-America

China-Europe

SE Asia-America

0.031
0.033
-0.022-0.0200.059**
0.058**
0.006(0.023)(0.022) (0.018)(0.023)(0.029)(0.026)(0.023)
Korea
0.034-0.040* 0.019-0.055** 0.025
0.033
0.011
(0.023)(0.024) (0.019)(0.027)(0.031)(0.029)(0.024)
Taiwan-0.063
0.007
0.001
0.071
-0.045-0.0590.020(0.046)(0.042) (0.033)(0.045)(0.046)(0.049)(0.039)South East Asia
0.023
0.036*
0.009
0.022
0.067*
0.063*
0.054**(0.025)(0.021) (0.023)(0.028)(0.035)(0.034)(0.021)
Europe-0.002-0.0180.030
0.014-0.023-0.0300.009(0.035)(0.030) (0.028)(0.034)(0.042)(0.042)(0.033)
North America-0.002-0.0170.010-0.005-0.004-0.0040.008(0.026)(0.025) (0.019)(0.020)(0.033)(0.031)(0.023)other countries-0.032-0.029-0.020-0.017-0.007-0.0230.005(0.031)(0.032) (0.025)(0.027)(0.035)(0.036)(0.028)Large cities
0.016
0.015
-0.001-0.002-0.000-0.009-0.017(0.025)(0.023) (0.021)(0.024)(0.031)(0.031)(0.025)
Medium sized cities
0.037
0.028
0.011
0.002
0.019
0.030
-0.008(0.023)(0.021) (0.020)(0.023)(0.030)(0.029)(0.024)
Small cities
0.038*
0.024
0.026
0.011
0.017
0.025
0.004
(0.021)(0.019) (0.018)(0.020)(0.028)(0.027)(0.022)
Constant-0.196** -0.135* -0.029
0.032-0.277*** -0.269*** -0.110(0.080)(0.072) (0.067)(0.083)(0.105)(0.099)(0.083)
No. obs
1996
1996
1996
1996
1996
1996
1996
R-squared
0.037
0.019
0.014
0.026
0.035
0.039
0.015
Inside brackets are robust standard errors. *,**,***= significant at the 10%, 5%, and 1% levels.

22

SE Asia
Europefrom
0.006(0.022)0.019(0.022)0.005(0.041)0.049**(0.021)
0.002(0.034)0.009(0.023)-0.010(0.029)-0.026(0.026)0.004(0.024)0.012(0.022)-0.102(0.079)1996
0.018