The Importance of Skin Colour in Central Eastern Europe: A Comparative Analysis of Racist Attitudes in Hungary, Poland and the Czech Republic

  • Published in:
    Central and Eastern European Migration Review, Vol. 11, No. 1, 2022, pp. 5-25
    DOI: 10.54667/ceemr.2022.03

    28 September 2021


    16 May 2022


    27 May 2022

    Views: 12077

The importance of skin colour is often neglected in empirical studies of negative attitudes towards minorities. In this study we use data from the 2014/2015 wave of the European Social Survey to analyse explicitly racist attitudes in Hungary, Poland and the Czech Republic. The data was collected before the refugee crisis of 2015–2016, which gives the study a unique opportunity to analyse these attitudes in three of the countries that were among the most hostile to migrants in the EU. The study demonstrates how theoretical perspectives commonly used in explorations of negative attitudes based on ethnicity may be effectively used to analyse racist attitudes. The results show high levels of racist attitudes in both Hungary and the Czech Republic, despite there being very few non-white immigrants in these countries, while, in Poland, the racist attitudes are less widespread. Realistic threats seem to be of little importance for understanding racist attitudes – in contrast, symbolic threats appear to be very important for understanding them. There is also the surprising result that voters for more moderate political parties are no less racist than voters for the more radical political parties in any of the three countries.


Keywords: racism, prejudice, Eastern Europe, attitudes, symbolic threat


Ethnicity and race can be viewed as two intertwined concepts, as they are both a form of social categorisation of human beings. They are socially constructed concepts which, at times, have been used interchangeably while, at other times, have been strongly differentiated (Spencer 2014). Max Weber (1978: 389) defined ethnic groups as ‘(…) those human groups that entertain a subjective belief in their common descent because of similarities of physical type or of customs or of both’. Contemporary definitions of ethnicity have changed somewhat from Weber’s original definition, with ethnic groups now largely being seen as groups of individuals distinguished by a common culture, often including language, religion or other patterns of behaviour or belief (Cornell and Hartmann 2007).

In Europe, race has very much taken a back seat to ethnicity, as race – and consequently racism – is strongly linked to the atrocities of the Hitler regime and the Holocaust (Lentin 2008). Race is difficult to define briefly as there is an absence of commonly agreed conceptual tools or a common framework for understanding the parameters of race (Murji and Solomos 2015). For this study, however, we use Cornell and Hartmann’s (2007) definition of race, understanding it as a group of human beings socially defined on the basis of their physical characteristics such as skin colour. We employ this definition as the core of our analysis is how majority populations perceive an outgroup based solely on skin colour.

It is important to note that race is far more complex than simply physical characteristics, as both cultural and religious aspects are important factors for the racialisation process of outgroups (see, for example, Garner and Selod 2015). There is a large number of quantitative studies exploring negative attitudes towards immigrants and minorities in Europe (Adnan 2020; Harris, Gawlewicz and Valentine 2019). However, there are surprisingly few quantitative empirical studies on explicitly racist attitudes in Europe.1 Instead, empirical studies exploring racial prejudice or race in Europe tend to use a dependent variable that measures attitudes towards minorities of a different race or ethnicity (Creighton, Schmidt and Zavala-Rojas 2019; Gorodzeisky and Semyonov 2015; Quillian 1995).

Another aspect relating to the issue of negative attitudes towards minorities in Europe is that studies tend to focus on the attitudes that can be found in Western European countries. This is not in itself surprising, seeing as the vast majority of immigrants live in Western European countries; it may therefore be of interest to focus on the dynamics between the majority population and the immigrant minority. However, although there are more immigrants in the Western half of Europe, higher levels of intolerance have been reported in the Eastern half (Bello 2017; Kunovich 2004, Strabac, Listhaug and Jakobsen 2012). There are different explanations for why this may be. Seeing that there are far fewer immigrants in Eastern Europe, one explanation may be that there is a lack of opportunity for contact with immigrants. In addition, these countries have had different historical experiences to Western Europe in regard to immigration and racism since the end of the Second World War (Humphreys 2000; Kunovich 2004; Law 2012).

We use the European Social Survey Round 7 (ESS7), collected in 2014–2015, to explore two major aims. The first is to explore whether the most common theoretical apparatus for studying prejudice based on ethnicity can advance explorations of racist attitudes based on an individual’s skin colour. The second is to explore the differences and similarities regarding factors that affect racist attitudes between Hungary, Poland and the Czech Republic. All three countries are members of the group known as the ‘Visegrad Four’2 or ‘V4’, who united against the EU during the refugee crisis of 2015–2016, refusing to admit a certain number of refugees. During the refugee crisis, Islamophobic and anti-migrant rhetoric was widespread and the display of a common front against the EU was previously unseen in European politics (Kalmar 2018). Interestingly, Hutter and Kriesi (2022) show that the refugee crisis was the first time that immigration was widely politicised in both Hungary and Poland. This makes the three V4 countries very interesting cases, as our data was collected before the crisis ‘hit’ Europe. It gives us a unique opportunity to explore the racist attitudes that we believe were already prevalent before the crisis and before the politicisation of immigration in the three countries.

Describing the contextual frames: The cases of Hungary, Poland and the Czech Republic

In order to understand the racist attitudes in Hungary, Poland and the Czech Republic before the refugee crisis, it is relevant to explain the contextual situation of the three countries; we therefore outline the political developments and the politics of immigration there. Furthermore, it is pertinent to identify potential outgroups in the three countries. Since the fall of communism, Hungary can be said to have experienced two phases: from 1990 to 2010, it was considered a liberal democracy while, after the landslide electoral victory for Fidesz in 2010, where the party gained over a two-thirds majority, it became what Prime Minister Viktor Orbán described as an illiberal democracy, where political power was increasingly centralised and the freedom of the people was being eroded (Biro-Nagy 2017). Since taking power in 2010, the right-wing party Fidezs, with Viktor Orbán as its leader, have been adamant that they will not ‘repeat the errors of the Western nations in setting their immigration policies’ (Korkut 2014: 624). Hungary, therefore, had a strict immigration policy and their immigrant share of the population at the time was around 5 per cent.3

Although Hungary did not have a large immigrant population, it did and still does have one of the largest Roma communities in Europe. Estimates of the size of the Roma population vary as it is difficult to measure but they are estimated to number somewhere between 300,000 and 700,000 (Ram 2014). Previous research on social distance shows that the Roma have traditionally been the most stigmatised minority group in Eastern Europe (Strabac et al. 2012) The Roma have also been discriminated against for decades in Hungary, including the deportation and killing of massive numbers of the Roma minority during World War II and the ongoing failure to recognise the Hungarian government’s involvement in this atrocity (Law 2012). Discrimination continued under communist rule, with the Roma being regarded as ‘brown’ Hungarians (Law and Zakharov 2019). The radical right party Jobbik were particularly harsh towards the Roma population (Kovács 2013).

In contemporary Hungary, racism and hate speech have also been incorporated into the discourse of the political elite. More recently, Muslims and refugees have been portrayed as the threatening ‘Other’ to Hungary’s identity, very much resembling the anti-Roma rhetoric previously used (Hafez 2018). Differentiating between ethnic Hungarians and the different outgroups is central to Orbán and Fidesz’ rhetoric, where the political messages which focus on the idea of an ethnically and culturally homogenic nation serve to unify the conservative support base of Fidesz (Bozóki and Simon 2019). While Fidesz took ownership of the migration issue during the refugee crisis, it was still considered a mainstream right-wing party at the time, while Jobbik was considered the more extreme and radical right-wing party (Bíró-Nagy 2022). This is an important distinction for the later discussion where we compare voters of the more radical right parties and the more moderate parties to see if there are any differences in racist attitudes between the voters of the radical parties and the voters of more mainstream political parties.

As with Hungary, Poland has also taken illiberal steps following the electoral victory of the right-wing populist Law and Justice Party (PiS). Both Fidesz and PiS use nationalist rhetoric and have been highly critical of EU integration, promising to defend their nation against the EU (Brusis 2016).

Before the refugee crisis, negative attitudes towards the different outgroups were prevalent in Poland (Gorodzeisky and Semyonov 2019). At the forefront were negative attitudes towards Muslims (Gorodzeisky and Semyonov 2019), despite the Muslim population in Poland making up less than 0.1 per cent in 2016 (Ipsos 2016). In fact, Poland was a highly ethnically homogenous society, with only 1.6 per cent of the population consisting of immigrants at the time. As with Hungary, these immigrants were also generally from neighbouring European countries. Scholars have asserted that Muslims began to be viewed as an external enemy soon after the fall of communism and especially after the terrorist attacks on 11 September 2001 in New York in which several Poles lost their lives (Pędziwiatr 2018). In addition, Poland’s participation in the war in Iraq and Afghanistan and the terrorist attacks in Madrid and London accelerated the anti-Muslim attitudes in Poland (Pędziwiatr 2018).

In the election year of 2013 in the Czech Republic, only 3 per cent of the population were satisfied with the political situation in the country and, as such, the centrist populist party ANO 2011 emerged (Havlik 2015).4 ANO 2011 can be viewed as more of a centrist populist party, with anti-corruption and anti-establishment at the forefront of its discourse, with party leader Andrej Babis stating that he wished to run the country as a business (Hanley and Vachudova 2018). ANO 2011 entered into a coalition with the social democrats after the 2013 election and won in 2017, still relying heavily on anti-establishment discourse (Leff 2019). In Hungary and Poland, both Fidesz and PiS heavily emphasised their nationalist rhetoric and moved towards an illiberal direction. ANO 2011, on the other hand, cannot be compared to these two parties, as they did not resort to nationalist rhetoric and the Czech nation still appears to be a robust democracy in its formal institutions (Hanley and Vachuvada 2018). The party constructed refugees and Muslims as an external threat and had a clear anti-immigration stance but these views were considered to be relatively mainstream in Czech politics (Hanley and Vachuvada 2018).

Following the Second World War, much of the multicultural Czech Republic disappeared. Millions of Germans were forcibly moved back to Germany and communist rule led to severe restrictions regarding immigration. From 2001 to 2007, the Czech Republic saw a significant increase in immigration, mainly due to a growing labour demand and an improving economic situation (Drbohlav 2012). Before the crisis, the Czech Republic had a similar proportion of immigrants to Hungary, with around 4 per cent of their population having an immigrant background. Like Hungary, the Czech Republic also has a somewhat long history of Roma discrimination. After the Second World War, only around 5 per cent of the Roma population survived in the country and, during the communist regime, the Roma were mainly given low-paid jobs, their children were sent to ‘special schools’ and there was a sterilisation scheme to reduce the birth-rate of Roma children (Law 2012). The Roma are still very much viewed as an unfavourable ethnic group, with 79 per cent of Czechs not wanting to have a Roma family as neighbours (Law 2012).

Another important aspect to keep in mind is the geographic location of the three countries and the way in which this affected how they faced external migration. The Czech Republic borders only EU countries and its immigrant population was also largely made up of EU citizens from neighbouring countries. Poland’s Eastern border is with Lithuania, Belarus and Ukraine, who also made up the biggest immigrant populations in the country (along with Germans). Furthermore, neither Poland nor the Czech Republic were on the main migration routes in 2015–2016. Hungary, however, was on the main migration route and was among the top receiving countries for asylum-seekers in 2015 (Valenta, Lønning, Jakobsen and Župarić-Iljić 2019; Valenta, Župarić-Iljić and Vidovic 2015).

The three countries all had a relatively low proportion of immigrants, especially those from outside Europe. However, intolerance towards the different ethnic outgroups were prevalent in all three countries, despite several of them being marginal in size (Gorodzeisky and Semyonov 2019). The exception would be the Roma population in Hungary and the Czech Republic. The two countries both have a long history of considering the Roma population as a ‘brown’ or ‘dark’ presence in need of being managed, regulated and controlled (Law and Zakharov 2019).

Another aspect is that all three countries have had populist parties win national elections. However, there is a difference between them. Whereas Hungary and Poland’s populist parties relied heavily on nationalist discourse, the discourse of ANO 2011 in the Czech Republic was primarily anti-establishment and anti-corruption.

Theory and previous research

Pettigrew and Meertens (1995) contend that Western Europe has developed a norm against blatant prejudice5 and that a more subtle prejudice has arisen. This is no different to what many scholars believe to be a shift to a new form of racism that centres on insurmountable cultural differences between groups – often known as cultural racism (Ramos, Pereira and Vala 2020). Cultural racism can be described as a more modern form of racism, where the focus is more on cultural differences between the majority and minority populations, rather than on biological differences (Balibar 1991). However, just because a ‘new’ form of expressing a racist attitude has emerged, this does not mean that the previous one has disappeared (Vala and Pereira 2018). Scholars such as Ramos et al. (2020) maintain that traditional forms of racism still persist in certain European countries; they further find that the more democracy is institutionalised, the more active are the different anti-racism norms. This finding has implications for our study. First, the social desirability bias6 may not be as prevalent in regard to racist attitudes in the three countries as it is in other Western countries, as they are relatively newly established democracies. The second is that the democratic backsliding which has happened in both Hungary and Poland leads us to believe that racist attitudes will be more prevalent in these two countries than in the Czech Republic.

Based on this overview, we explore the differences and similarities in what affects racist attitudes between Hungary, Poland and the Czech Republic. We are primarily interested in analysing the more blatant forms of prejudice in this study. Therefore, for our purposes, a racist attitude is understood as a negative attitude towards a minority group defined solely by its physical appearance. To analyse racist attitudes in Hungary, Poland and the Czech Republic, we use two theoretical approaches: intergroup threat theory and intergroup contact theory. Intergroup threat theory explains the different threat perceptions that individuals or groups may have in relation to immigrants (Stephan, Ybarra and Rios 2016). An earlier version of this theory was named integrated threat theory and included four forms of threats (see Stephan and Stephan 2000).7 In the more recent version of this theory, researchers distinguish between realistic threat8 and symbolic threat (Stephan et al. 2016).

Concern over physical harm or the loss of material resources can be categorised as realistic threats. At a group level, realistic threats are related to the in-group’s power, resources and general welfare while, at an individual level, the category of the realistic threat concerns material, economic, physical and security threats to an individual group member (Andersen and Mayerl 2018; Billiet, Meuleman and De Witte 2014; Hainmueller and Hiscox 2010; Nunziata 2015).

Symbolic threat is, on the other hand, at a group level linked to perceived threats to the in-group’s religion, belief system, values or ideologies while, at an individual level, the symbolic threat is often linked to an individual’s self-identity or self-esteem. Symbolic threat can be exemplified by individuals’ perceived threat to their country’s cultural identity by immigrants. It is argued in some studies that these symbolic threats are often more important than realistic threats in predicting anti-immigrant attitudes (Lucassen and Lubbers 2012).

Previous studies have examined how different threats are linked to different minority groups. Ben-Nun Bloom, Arikan and Lahav (2015) found that, in Europe, symbolic threats are linked more to immigrants who are racially and ethnically different, while realistic threats are connected more with immigrants who are racially or ethnically similar. In the same vein, Gorodzeisky (2019) posits that Eastern Orthodox individuals in Russia tend to oppose the immigration of ethnically or racially different immigrants who are a threat to their cultural homogeneity and national identity. Furthermore, in their study of biological racism across Europe, Vala and Pereira (2018) highlight that new theoretical models which emphasise more symbolic and ideological dimensions, rather than socio-positional variables, should be used to understand the persistence of biological racism in Europe. We therefore expect the symbolic threat perceptions to be more important in understanding the racist attitudes in the three countries. However, as we explained in the contextualisation section, immigrants who are ethnically and racially different were, at the time, almost non-existent in the three countries so it is somewhat unclear how the different threat perceptions may play a part in the racist attitudes.

A moderator of these negative attitudes can be intergroup contact, deriving from Gordon Allport’s (1954) contact hypothesis, which posits that if there is i) equal status within the contact situation, ii) cooperation between the groups, iii) common goals and iv) support from the government, contact will reduce prejudice towards out-groups. More recently, these four criteria have been found not to be essential, although they do contribute to the reduction of prejudice (Paluck, Green and Green 2019; Pettigrew and Tropp 2006). However, it is maintained that negative contact and competition between groups may increase intergroup prejudice (Dovidio, Gaertner and Kawakami 2003; Paolini, Harwood and Rubin 2010). Intergroup contact can also moderate perceptions of threat as, when contact is established, increased empathy and knowledge and decreased anxiety towards the outgroup most likely influences the extent to which vulnerable individuals perceive outgroup members as threatening (Thomsen and Birkmose 2015). Intergroup contact can therefore reduce threat perceptions which, in turn, can reduce anti-immigrant attitudes (Schlueter and Wagner 2008).

An important aspect to consider in regards to intergroup contact in Hungary, Poland and the Czech Republic is that they all have small immigrant populations and even smaller racially dissimilar immigrant populations. The opportunity for contact is therefore severely limited in these countries. What can further complicate intergroup contact in Hungary are the larger Roma populations who represent the Hungarian ethnic ‘other’ (Csepeli and Simon 2004; Koulish 2003; Vidra and Fox 2014). We highlight this possible factor as some studies have found that casual contact with Roma minorities tends to have a negative effect on attitudes in Eastern Europe (Kende, Hadarics and Lášticová 2017; Visintin, Green, Pereira and Miteva 2017). The effect of contact in Hungary may therefore be somewhat more complex than in the other two countries.

Despite the issues that we may face with intergroup contact theory, we still maintain that it is a valuable approach as we may gain insights into the effect of contact – or its absence – on racist attitudes in societies where the opportunity for intergroup contact is less likely. Nevertheless, contact with a minority is still expected to have an effect in all three countries, which actualises important differences in experiences – such as the difference between having no contact and having some contact. Based on the above-mentioned studies, we therefore explore the various dimensions of intergroup contact and perceived real and symbolic threats on racist attitudes in the three contexts.

Data and methods

This study uses data from the seventh wave of the European Social Survey (ESS) collected in 2014–2015. The dependent variable for this study is based on the following question from the survey: ‘Please tell me how important you think each of these things should be in deciding whether someone born, brought up and living outside [country] should be able to come and live here. Please use this card. Firstly, how important should it be for them to be white?’ The respondents then ranked how important they believed it was that the immigrant should be white on a scale ranging from 0–10 where 0 represents extremely unimportant and 10 is extremely important. We believe this variable accurately measures overt racism as it explicitly asks the respondents how important skin colour is in accepting an immigrant to their country. To analyse the data, we used a linear regression model in the three selected countries. The sample size is a total of 4,122 respondents, of whom 1,255 are from Hungary, 1,230 from Poland and 1,637 from the Czech Republic. The estimates are weighted using post-stratification weights.

An interesting aspect regarding the data analysed is the period in which it was collected. The largest fraction of the data collection in Hungary took place in May 2015; in Poland it was in May and June 2015 and in the Czech Republic it was in December 2014 and January 2015.9 The data was thus collected before the refugee crisis of 2015 had escalated to its full scale between August and December 2015. This gives us a unique opportunity to analyse the already existing attitudes in the three countries before the height of the refugee crisis.  

As this study aims to explore whether the theoretical framework usually applied in studies of ethnic prejudice can be effectively used in a racial framework, the independent variables chosen for this study all have a basis in previous research and theory exploring ethnic prejudice. Therefore, gender (female=1), age (measured in years), education (measured in years) and how urban or rural the respondents’ lives were (on a scale of 1–5) have been included as they have all been found to be important for explaining ethnic prejudice (see Ceobanu and Escandell 2010 for review). Gender and education have also been found to be predictors of racist attitudes in Europe (Caller and Gorodzeisky 2021). For threat perceptions, we have chosen six individual-level characteristics which may serve as indicators of threat perceptions or increases in the level of perceived threat from non-white immigrants. Unemployed (1=employed), income (1–4) and country economy (0–10) are three variables that are chosen to represent economic aspects of the realistic threat category (Stephan et al. 2016). Unemployed individuals are expected to be more hostile to immigrants, as they may perceive the latter as competition for jobs. Income measures how satisfied the respondent is with his or her household’s income. Individuals who are not satisfied with their income may perceive immigrants as a threat to them achieving a better income. Country economy measures how satisfied the respondents are with the present state of the economy in their country. We expect individuals who are less satisfied with their country’s economy to be more racist, as immigrants of a different skin colour may be perceived as a threat to their country’s economy which, in turn, could mean a reduction of benefits, higher taxes, etc. As for a security aspect in realistic threat, we use the variable safety (1–4), which measures the respondent’s feeling of safety when walking alone after dark. In line with previous studies, we expect that individuals who feel less safe will feel more threatened by non-white immigrants, as they may perceive them as either stereotypically criminal or terrorists (see Andersen and Mayerl 2018; Billiet et al. 2014; Hainmueller and Hiscox 2010; Nunziata 2015).

The symbolic threat of intergroup threat theory features two individual-level variables in this analysis: customs (1–5) and religiosity (0–10). Customs asks the respondents how much they agree with the following statement ‘It is better for a country if almost everyone shares customs and traditions’. We expect individuals who believe it to be better for a country if almost everyone shares customs and traditions to be more racist, as the foreign culture of non-white immigrants may be perceived as a symbolic threat to local customs and traditions. We expect similar results for the variable that measures how religious the respondents view themselves. Individuals who regard themselves as very religious may view non-white immigrants as a symbolic threat to their Christian culture and heritage. As previous studies have shown, symbolic threats are very much linked to ethnically or racially different immigrants (Ben-Nun Bloom et al. 2015; Gorodzeisky 2019). Therefore, it will be interesting to see whether racist attitudes in the three countries are linked more to symbolic than to realistic threats.

As all three countries have seen a rise of right-wing populist parties, we have chosen to include three political variables which may be of interest; Political trust10 (0–10), EU too far (0–10) and Party last voted for. In regards to political trust, we expect individuals who have lower levels of political trust to have a more racist attitude, as populist politicians often blame the establishment and immigrants for the problems in their respective countries (Bugaric and Kuhelj 2018). EU too far asks the respondents if EU integration has gone too far or if it should go further. We have added an EU variable because both Fidesz and PiS have been critical of EU integration. Respondents who distrust the EU may do so because they identify entirely with their nation state and the EU can be seen as a ‘cause’ of non-white immigration to their country (Brosius, Van Elsas and De Vreese 2019). As both Hungary and Poland have taken an illiberal turn in recent years, it would also be of interest to identify differences between the voters in the three countries, which is why we have added a variable showing us which party our respondents voted for in the last election.

Finally, two contact variables have been added. Contact measures how much contact the respondents have with a person of a different race or ethnic group.11 The original variable had seven categories; however, as previously mentioned, there are limited opportunities for contact with minorities in the three countries, which skews the distribution of the variable somewhat. We have therefore recoded the variable into three categories (1=Never, 2=Some 3=Often). We also have a variable measuring whether the respondent lives in an area with people of a different race or ethnicity (0=Almost nobody, 1=Some/many). As with the previous contact variable, this has also been recoded from three to two categories, as the variable is somewhat skewed, particularly in Poland.


In Figures 1a, 1b and 1c, we show a simple distribution of the dependent variable so that we can analyse the differences concerning the levels of racist attitudes that can be found between the three countries.

From the three figures, we can see that there are high levels of racist attitudes in Hungary, with almost as many respondents believing that it is extremely important that the immigrants be white as those who believe the opposite. Comparatively, the results in Poland are a great deal lower than in Hungary and the Czech Republic, as there are surprisingly high levels of racist attitudes in the Czech Republic, very comparable, in fact, to those that can be found in Hungary.12

Figure 1a. Distribution on the dependent variable in Hungary

Source: Based on results from ESS Round 7 (2014).

Figure 1b. Distribution on the dependent variable in Poland

Source: Based on results from ESS Round 7 (2014).

Figure 1c. Distribution on the dependent variable in the Czech Republic

Source: Based on results from ESS Round 7 (2014).

An important aspect to comment on is the fact that there are high levels of racist attitudes towards immigrants of a different skin colour, despite there being very few immigrants in any of the three countries – the figures also show us that, even before the refugee crisis, there were extremely high levels.

We have explored the above-mentioned differences in more detail in Table 1, which includes two OLS models. We observed that previous relevant models that did not include symbolic variables had relatively low explanatory power (Vala and Pereira 2018). Therefore, we have chosen to exclude our symbolic variables from Model 1 and include them in Model 2 in order to see the differences in explanatory power of the models. When analysing the results, we mainly focus on Model 2, unless there are specific aspects regarding Model 1 that require commenting on.

Table 1. Linear regression models of racist attitudes in Hungary, Poland and the Czech Republic

Note: standard errors in parentheses * p < 0.05, ** p <0.01, *** p < 0.001.

We begin our analysis by commenting on the differences in R2 between Models 1 and 2. In Model 1, Hungary and Poland have an R2 of 0.134 and 0.110, whereas the Czech Republic has an R2 of 0.058. When we introduce the two symbolic variables into Model 2, we see a considerable increase in all three countries, with an R2 value of 0.185 and 0.197 in Hungary and Poland respectively and an R2 value that is doubled in the Czech Republic to 0.117. This indicates that the symbolic variables are very important for understanding the racist attitudes we find in the three countries. Customs has a relatively strong effect in all three countries and shows us that individuals who believe that everyone should share the same customs in a country are more likely to have a racist attitude towards non-white immigrants. A greater discussion surrounding the effect of customs will take place later in the paper.

Religiosity has an effect in Poland, showing us that individuals who are more religious are more prejudiced towards non-white immigrants. In a European context, The Czech Republic can be characterised as highly secular, Hungary as somewhat religious and Poland as highly religious (Pew Research Center 2018). This may account for why religiosity has only a statistically significant effect in Poland since religion holds a strong position in Polish society. Some researchers explain the idea that the more religious Poles are, the stronger the racist attitudes they harbour will be, due to an ongoing trend of intensified sacralisation of the nation and an intertwining of Catholicism with Polish nationalism (Pędziwiatr 2018).

Following the effects of the symbolic variables, we start analysing the other variables from the top (see Table 1). The analysis shows that the female variable does not have any effect in any of the three countries. It is also evident that age has an effect in Hungary and Poland, showing that older individuals have more racist attitudes. However, age does not have an effect in the Czech Republic.

Furthermore, there is an interesting aspect regarding the estimates of education. Education cannot be said to have a statistically significant effect in Poland, which is surprising as education’s role in defeating prejudice is one of the more robust findings across studies in the field (Ceobanu and Escandell 2010). Urban has an effect in both Hungary and the Czech Republic; however, there is a different direction in the effect between the two countries. Living in more urban areas is associated with less racist attitudes in the Czech Republic. In contrast, living in more urban environments is associated with higher levels of racist attitudes in Hungary. Safety cannot be said to have an effect in any of the three countries, showing us that non-white immigrants are not necessarily perceived as a security threat. The two contact variables show interesting effects in the three countries. Contact has a statistically significant effect in all three countries; however, it influences the racist attitudes differently in each of them. Having some or often having contact with an individual of a different race or ethnicity is found to have a decreased effect on racist attitudes in Poland. In the Czech Republic it is only for individuals who often have contact that the same effect can be found. Surprisingly, in Hungary contact has the opposite effect, as individuals having some or often having contact with a different race or ethnicity are associated with higher levels of racist attitude. This is explored further in the section discussing the findings. While often having contact with ethnic and racial outgroups decreases racist attitudes in the Czech Republic, living in areas with different ethnic and racial minorities increases racist attitudes there.

The three economic variables unemployed, income and country economy were expected to show signs of perceived realistic group threat. Several previous studies on the topic indicate that vulnerable groups, such as blue-collar workers or unemployed people, may view immigrants as a competitive threat to their jobs (Billiet et al. 2014; Hoxhaj and Zucotti 2021; Kunovich 2017). Other group-threat contributions show that immigrants are either perceived as a burden on a country’s economy (Hainmueller and Hiscox 2010) or indicate a perceived connection between immigrants and higher crime levels (Nunziata 2015). However, we cannot see in our models that being unemployed has an effect on the racist attitudes in any of the three countries. An individual’s satisfaction with their income level has a negative effect in the Czech Republic, telling us that the more satisfied an individual is with his or her income, the less racist the attitude they hold. Yet, individuals in Poland who are satisfied with the economy in the country will hold a more racist attitude than individuals who are less satisfied with the economy. In light of realistic group threat studies in other countries, we expected the opposite effect, as a perception of a weak economy was expected to lead to a perception of non-white immigrants as a reason for it or that an increasing inflow of non-white immigrants could be perceived to lead to a reduction in benefits or an increase in taxes. This turned out to be an incorrect assumption, as it had no effect in Hungary or the Czech Republic and had the opposite effect in Poland.

Political trust has no effect on racist attitudes in any of the three countries, while EU too far has a positive effect in both Hungary and Poland, meaning that the more sceptical individuals are of the EU in Hungary and Poland, the more racist the attitude that they would have. In 2014, EU integration was an important issue in party competition in both Hungary and Poland, with the two largest populist parties, Fidesz and PiS, both being critical of EU integration (Brusis 2016). Fidesz and PiS have both promised to defend their nation against the EU while, in the Czech Republic, the biggest populist party, ANO 2011, has largely had a more technocratic populism, with corruption as the main ‘enemy’ rather than a nationalistic populism as in Hungary and Poland. ANO 2011 leader Andrej Babis was not a staunch Eurosceptic, as he favours the EU market structure (Hanley and Vachudova 2018).

There are surprising results when exploring the party voted for variable. The reference category for each country includes parties that are generally considered to be the ‘most’ populist and radical-wing political party.13 There are two findings we wish to comment upon when analysing the party voted for variable. The first is the number of statistically significant categories. When compared to Jobbik, PiS and ANO 2011, there are a total of six out of 20 categories that have a statistically significant effect; four of these categories involve respondents who did not vote or refused to state which party they voted for. The remaining two categories are the centre-right and highly anti-immigrant party Fidesz and the social-democratic ČSSD, whose voters display lower levels of racist attitudes than the radical right-wing populist parties in their respective countries. It is remarkable that none of the voters for the centre-left or left-wing parties in either Hungary or Poland can be said to be statistically significantly less racist than the voters for Jobbik or PiS, even after controlling for several variables. It does, therefore, appear that these attitudes could be found across the political spectrum in the three countries.


Our exploration of racist attitudes has resulted in several very interesting findings that may be roughly divided into two categories. In the first category are findings that confirm previous studies on racist attitudes, while the second includes more unexpected findings. The magnitude of the openly racist attitudes that can be found in Hungary and the Czech Republic and the difference between these two countries and Poland are what stand out.

An often-cited methodological problem in survey research is that of the social desirability bias (Krumpal 2013), as respondents have a tendency to under-report attitudes that conflict with the prevailing norms of society. It may appear that these norms are somewhat lacking in both Hungary and the Czech Republic and it is remarkable that so many of the respondents openly admit to having a racist attitude.

Previous studies have found that symbolic threats are more connected to immigrants of a different race or ethnicity, while realistic threats are more connected to immigrants of the same race or ethnicity (Ben-Nun Bloom et al. 2015; Gorodzeisky 2019). This study largely finds this to be the case with the explicitly racist attitudes shown here, where realistic threats seem to have little or no effect in the three countries. Even the more economic side of realistic threats has almost no effect in the three countries. None of the economic variables have any effect in Hungary, indicating that realistic threat perceptions are not a factor in explaining the racist attitudes there, while only one economic variable has an effect in the Czech Republic and Poland. It is, however, important to consider that the dependent variable used for this study does not measure anti-immigrant attitudes in general but the importance of immigrants being white. One can assume that all immigrants in general, regardless of their skin colour, will be perceived as economically threatening to economically vulnerable individuals. Therefore, these individuals will not necessarily have a preference for white immigrants.

Symbolic threat, on the other hand, can be viewed as a very important factor for the racist attitudes in the three countries. This follows Ben-Nun Bloom et al.’s (2015) finding that culturally threatened individuals prefer immigrants who are similar to themselves. The perception of not having shared customs and traditions has a strong effect in all three countries. It is also a very important variable for understanding the racist attitudes in all three countries, which is also indicated by the considerable rise of the explanatory power of the statistical models. It does, therefore, seem that, even though we are measuring negative attitudes towards a minority based solely on skin colour, a perceived cultural threat is very much connected to these negative attitudes. In other words, it seems that, when an individual who harbours a racist attitude views a person of a different colour, the racist individual will also perceive this person as culturally different.

Regarding intergroup contact, there is somewhat of a conundrum here as it has the expected effect in both Poland and the Czech Republic but it has an unexpected one in Hungary in that contact equals a more racist attitude. A possible explanation for this is that, as mentioned above, Hungary has one of the largest Roma-minority populations in Eastern Europe. We may therefore expect that much of the contact that is had with another race or ethnic group is with an individual of Roma origin. We highlight this fact, as some studies have shown that contact with the Roma tends to have a negative effect in Eastern Europe (Kende et al. 2017; Visintin et al. 2017).14 We have previously described Hungary’s and the Czech Republic’s long history and continued discrimination against their Roma minorities. One may therefore speculate whether these sentiments towards their Roma populations simply found a new target in the face of the arrival of irregular migrants in 2015.

Last but not least, we have also explored the effects of political parties on people’s attitudes. Previous studies indicate that voters for more right-wing political parties tend to be more sceptical towards immigrants (Callens and Meuleman 2017) and that populist politicians tend to blame immigrants for the problems which their country is facing (Bugaric and Kuhelj 2018). It was therefore our expectation that there would be a statistically significant difference between voters for the more radical populist parties and voters for mainstream political parties with regard to their attitudes towards minority populations. It was therefore unexpected that we found no statistical difference in the racist attitudes between voters for right-wing populist or extremist parties in the case of Jobbik and other parties, apart from Fidesz in Hungary and ČSSD in the Czech Republic.


To summarise, this study demonstrates that the theoretical approaches we chose to use can be applied effectively to studies of racist attitudes, showing that symbolic threats are very important for understanding these attitudes. People with a different skin colour are often automatically attributed a difference of culture. Realistic threats, on the other hand, seem to be of less importance, although we cannot say for certain that the same results would be produced in a country with a higher percentage of non-white immigrants. However, we also acknowledge that there are some mixed and counterintuitive results with regards to intergroup contact theory and the effects of the political parties.

One highly important finding is that these racist attitudes were prevalent before the refugee crisis in 2015–2016. This was particularly so in the Czech Republic and Hungary. It therefore seems that there was already a fertile background of racism – and not necessarily manipulation by populist politicians – that prepared the foundations of the political response to irregular migration. This is also clear when one considers that, generally, voters across the political spectrum in all three countries seem to harbour similar racist attitudes. The political parties also seem to have taken advantage of this, as several studies have highlighted how, across the ideological spectrum, they were all hostile to migrants across Central and Eastern Europe (Hanley and Vachuvada 2018; Korkut 2020).


1 Notable exceptions include Vala and Pereira (2018), Ramos et al. (2020) and Caller and Gorodzeisky (2021).

2 Slovakia is the fourth member of the Visegrad Four. Unfortunately, Slovakia was not included in the dataset that is used in this study.

3 All numbers relating to immigrant size and make up are extracted from the UN international migrant stock and can be found at: (accessed 21 May 2022).

4 Dawn of Direct Democracy (Dawn) was another populist party which emerged, gaining 6.9 per cent of the votes, although several MPs and the party leader, Tomio Okamura, split to form another right-wing populist party – Freedom and Direct Democracy (SPD). Dawn was dissolved in 2018.

5 They define blatant prejudice in its full form as a belief in the outgroup’s genetic inferiority.

6 The social desirability bias refers to making oneself look good in terms of prevailing cultural norms when answering specific survey questions (see Krumpal 2013 for a review).

7 The four threats originally included were: realistic threat, symbolic threat, intergroup anxiety and negative stereotypes (see Stephan and Stephan 2000 for the original ‘Integrated Threat Theory of Prejudice’).

8 Realistic threat does not necessarily have to be a ‘real’ threat, as intergroup threat theory is primarily concerned with the perceptions of threat, as perceived threats have real consequences, regardless of whether or not the perceived threat is actually real (Stephan et al. 2016: 258).

9 The official data collection period in the three countries was from April to June in Hungary, November to February in the Czech Republic and April to September in Poland. The data collected in August and September in Poland only make up 1 per cent of the sample there and should not affect the overall data.

10 Political trust was constructed using five variables: i) trust in country’s parliament, ii) trust in the legal system, iii) trust in the police, iv) trust in politicians and v) trust in political parties. The constructed variable had a Cronbach’s Alpha score of 0.91 in Hungary, 0.86 in Poland and 0.91 in the Czech Republic.

11 There are different measures for contact in the dataset; there is another variable measuring how good or bad the contact is between the respondent and people of a different race/ethnicity. The disadvantage with this variable is that there are very few immigrants in the three countries. As such, a large number of respondents (over 50 per cent in Poland) have never had contact with an individual of a different race/ethnicity and would therefore be excluded from the analysis. We have thus chosen to use the variable measuring the amount of contact with a minority as it is of interest to include the respondents who have never had contact with a minority.  

12 To contextualise the result, we have added the average racist attitudes across Europe in Appendix A1. It is clear that racist attitudes are considerably more pronounced in the three countries than in Western Europe. Estonia and Lithuania were the only two countries with a greater amount of racist attitudes, which indicates a considerable difference between the attitudes that can be found in Eastern European countries compared to Western Europe.

13 The exception here would be in the Czech Republic, where ANO 2011 is the reference category. While ANO 2011 is certainly a populist party, the most right-wing populist party in the Czech dataset would be Dawn; however, as they only make up 1.65 per cent of the respondents, we have chosen ANO 2011, with 14.23 per cent of respondents, as the reference category.

14 What complicates this explanation is that the Roma population in Hungary tends to live in more rural areas and the variable urban found that rural Hungarians actually have less racist attitudes than more urban counterparts. Future research should therefore focus more on the rural/urban situation.

Conflit of interest statement

No conflict of interest was reported by the authors.


David Andreas Bell

Zan Strabac

Marko Valenta


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Appendix A1

Figure A1. Average racist attitudes in Europe (0/10)

Source: Based on results from ESS Round 7 (2014).

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