Keywords

Introduction

Ethnic and racial discrimination violates the basic human right to equal opportunity, adopted by the United Nations in the Universal Declaration of Human Rights in 1948. Discrimination is a threat to the cohesion of society and leads to the exclusion of some people. To combat discrimination, we must understand its extent, how it manifests, and how it can best be counteracted. Such knowledge is even more important during times of crisis since vulnerable people are even more exposed and helpless during difficult periods. The Covid-19 pandemic is one of the most challenging global experiences of humankind in modern history, with severe global health-related (Mallah et al., 2021) and economic consequences (Brodeur et al., 2021), as well as far-reaching effects on most other aspects of our lives (Onyeaka et al., 2021). Some efforts have been made to study how the pandemic has affected ethnic and racial discrimination across various societies. The purpose of this chapter is to provide an overall picture of this evidence.

We concentrate mainly on research that provides conclusive evidence of discrimination during the Covid-19 pandemic. Research results from the labor market, the housing market, as well as other contexts are presented. Our point of departure is the economic theory of discrimination and economic methodologies for measuring discrimination. Therefore, this chapter adopts the economic definition of discrimination. Hence, with ethnic or racial discrimination, we mean differential treatment of a person with an ethnic or a racial minority background even though the person has the same characteristics as a person belonging to the ethnic or racial majority. What is meant by ethnicity or race is a research question in itself. For simplicity, we henceforth only use the term ethnicity to refer to both an ethnic or a racial minority background—regardless of whether a person is first- or second-generation immigrant, Christian or Muslim, Kurdish or Turkish, Black or White, American or European, and so on. We are aware that these differences and nuances certainly matter and are important when studying discrimination. Our focus in this chapter is, however, to analyze the effects of the Covid-19 pandemic on ethnic and racial discrimination in a general sense rather than specific to a certain categorization.

Economic Theories of Discrimination

Why does discrimination exist? Several economic theories have been advanced to explain the phenomenon (Lundahl & Wadensjö, 1984). We focus on three: monopsony, tastes (preferences or prejudice), and statistical discrimination.

Monopsony

The oldest of the theories that concern us here is that of the discriminating monopsonist, developed by Robinson (1932). Assuming that the monopsonist has a choice between two categories of equally productive labor but with different wage elasticities of supply, in order to maximize profits, he will equal the marginal cost of hiring each category and the total marginal cost obtained by adding the two labor supplies with the demand price of labor. The result is that the group with the highest elasticity receives a higher wage than the other group. If one of the groups is organized, the same conclusions apply. The organized group, offering its labor at a given wage rate, will receive a higher wage than the unorganized group.

The monopsony model offers an analysis of how discrimination works and of its results. The interest in the effects of monopsony is increasing. For a survey, see Manning (2021) and for a study of the relationship between monopsony and the effects of migration on wages, see Amior and Manning (2021). It is likely that monopsony together with other forms of discrimination lead to larger effects than monopsony alone.

Taste-Based Discrimination

The idea of preferences, or tastes for discrimination, was introduced by Becker (1957). Individuals have preferences for making economic transactions with some people but not with others and are prepared to accept an economic loss because of this. Becker expressed tastes by introducing a discrimination coefficient, d. If the going wage is w, the discriminating employer acts as if it were equal to w(1 + d), where wd is the non-monetary cost of hiring a particular individual.

This approach works if all employers have the same preferences, but once we allow for different d:s for different employers, complications arise. In the first place, discrimination will lead to segregation. With two labor categories in society that are perfect substitutes and prejudices against one group, employers with low d:s will hire the latter group while employers with high d:s will hire the other group. This will lead to wage rates that tend to be the same for both groups. Discrimination will become unstable. Employers with weaker preferences for discrimination will produce at lower perceived costs and make larger profits than those with stronger preferences, and hence drive the latter out of the market.

Becker analyzed the results of discrimination in a model with two different societies: one white and one black. They produce the same single good with the aid of labor (white and black, respectively) and capital. The latter is mobile between the two sectors and the white economy exports capital to the black one. Assuming that white capital owners develop a prejudice against black labor, they will reduce capital exports. Black capitalists will make a gain and black workers will lose, due to the lower capital-labor ratio, while white capitalists will lose and white workers gain since this ratio increases in white society. However, this analysis contains a flaw. Preferences for discrimination do not remain constant. What is compared is one situation where no prejudice exists and another where the capitalists are prejudiced against blacks, and this violates one of the fundamental postulates of welfare economics. It is not possible to compare situations with different tastes. The yardstick must remain constant. It can, however, be shown that if tastes are held constant, it may pay for white capitalists to act according to them, provided that the psychic gains are positive and outweigh the monetary losses.

The original Becker formulation identifies white capitalists as the group that possibly discriminates against black workers. When viewed in terms of common sense, this is somewhat puzzling, since capital owners stand to gain from cheap labor. This presumption is borne out once the model is reformulated in purely pecuniary terms, so as to exclude tastes for discrimination. Then white capitalists lose if they withdraw capital from the black sector while the white workers make a gain, since they compete directly against their black counterparts. Thus, we should expect white workers to favor discrimination and white capitalists to be against it. Further, it is much more likely that labor is the mobile factor, rather than capital, so that black and white laborers work side by side in the white economy and discrimination takes the form of a reduction in the number of blacks allowed to enter the latter. Provided that blacks and whites receive the same wage in the white sector, again, white capitalists make a loss while white workers gain.

Discrimination due to taste may also be caused by white worker preferences against working with black workers (or native preferences against working with workers from ethnic minorities). If white and black workers are perfect substitutes, the result may be segregation: white and black workers work in different workplaces. If white and black workers are not perfect substitutes (e.g., have different educations or occupations), the result is wage differences.

A third form of discrimination due to preferences is that consumers may have preferences against black workers and, hence, avoid buying goods and services if the employees are black. It leads to a lower demand for black workers in jobs where the employees have contacts with the customers and, subsequently, to occupational segregation and lower wages for blacks.

The conclusion to be drawn from the reformulated Becker model, without tastes, is that it is hardly the capitalists/employers who stand to gain from discrimination, but the workers competing with their discriminated colleagues. However, this is hardly a realistic portrait of the situation prevailing in many contemporary societies, where the situation often is that people who can be identified by their ethnicity or religion are excluded when it comes to hiring. Thus, other theories are needed to explain the rationale.

Statistical Discrimination

One such theory is that of statistical discrimination (Phelps, 1972; Arrow, 1973). The point of departure is that employers possess only imperfect information about the productivity of the labor force and, therefore, are forced to base their decisions on proxies, like group membership (‘having the same school tie’). One variety of statistical discrimination is based on the use of information on the average productivity of different groups, for instance, information on education. Which school you come from and the level attained could act as a signal of the expected productivity of a job applicant (see Spence, 1974). Persons and groups with a higher expected productivity are hired to a greater extent.

However, some groups display a larger variance than others, which means that the productivity of individual members of these groups may be well below the average and not correspond to the wage that they will receive. This provides an incentive for risk-averse employers to avoid hiring members of certain groups so as to minimize the risk of ending up with ‘lemons’; a procedure that will discriminate against group members with average or higher productivity.

The Extent and Measures of Discrimination

Discrimination against ethnic minorities may lead to differences in wages and working conditions as well as to segregation. Many studies have been made of the existence of wage differences and such wage differences are also found. However, the differences are not necessarily proof of discrimination, and discrimination may exist even if no differences are found with such a method. More sophisticated methods are needed. We will discuss research in this field related to the theories of discrimination, beginning with studies of wage differences and continuing with studies of segregation.

Wage Differences

When studying wage differences with the purpose of comparing the wages of natives and ethnic minorities, it is very important to control for other characteristics, including age, gender, education, and region (van der Meulen Rodgers, 2006). In many cases, a difference is found even after such controls are made. These differences may be due to various forms of discrimination, such as preference-based discrimination, statistical discrimination, or monopsony. Preference-based discrimination and statistical discrimination may force ethnic minorities to accept a lower wage in order to be hired. Monopsony power may induce employers to offer lower wages in a situation where people from ethnic minorities do not have any possibilities to find a better paid job elsewhere.

Wage discrimination and wage differences may not be of the same magnitude across all occupations. Ethnic minorities may not, for example, be discriminated against in some low-qualified occupations but discriminated in others; in other words, there may exist a glass ceiling for ethnic minorities, or, if you like, an occupational wall.

In an economy, such as Sweden, with strong unions and wage negotiations covering most parts of the labor market, it is very likely that the wage differences between employees who have the same occupation or work in the same company are smaller than in countries with weak unions (for a thorough discussion on trade unions and the foreign born in Sweden, see the chapter in this book by Bender, 2023). If there are no or only small differences, the employers have weaker incentives to hire people from ethnic minorities than in economies with larger wage differences. The main differences may instead be found in recruitment behavior, which leads to differences in unemployment and, thereby, also to segregation.

Segregation

To a large extent, ethnic minorities and natives work in different occupations. This is easily seen from labor market statistics. There are several explanations for that. Differences in the type of education and differences in preferences for different types of work and occupations are only two of them. However, discrimination in the hiring process may also be an explanation. A number of studies of this process have been undertaken.

One frequently used method is for researchers to send fake applications to a large number of vacant positions (Bertrand & Duflo, 2017). In some of the applications the name signals that the person belongs to an ethnic minority, in other applications to the same position the name signals that the applicant belongs to an ethnic majority. Generally, the result is that applicants belonging to the ethnic majority are invited to the company for an interview more often than applicants from an ethnic minority. However, differences do exist between various occupations.

A second method is to let applicants (in practice actors) go to interviews with the hiring firm if they are called and see what happens: do they get a job offer or not and is there any difference depending on if the applicant belongs to an ethnic minority or not (Riach & Rich, 2002)?

A third method is to use vignettes. Studies based on vignettes consist of fictitious cases where participants are asked to reflect on a particular situation as if it were a real one. It is a kind of a thought experiment. An employer taking part in a study gets a number of applications and is asked who would have been invited to an interview if there were a vacant position. There are variations in the characteristics of the applicants presented, one of which is whether they are an ethnic minority or not (Eriksson et al., 2017).

So far, we have only discussed discrimination in the labor market, but there may also be other forms of discrimination, some of which lead to segregation, as in the housing market. Those trying to find an apartment may be discriminated against if they are an ethnic minority. This could be part of the explanation for housing segregation. The same types of methods used to study labor market discrimination have also been used in studies of the housing market (Riach & Rich, 2002; Bertrand & Duflo, 2017). They confirmed that this form of discrimination leads to segregation. Housing segregation may also have indirect effects on labor market discrimination and segregation. Living in an area that displays social problems may lead to discrimination when applying for a job.

Finally, there are many ways of testing for discrimination in the laboratory (Anderson et al., 2006). Laboratory experiments are typically used to test specific hypotheses and to evaluate specific mechanisms related to discrimination. One example is Fershtman and Gneezy (2001), who separated taste-based and statistical discrimination in their analysis.

Covid-19 Pandemic and Ethnic Discrimination

The Covid-19 pandemic may have important implications for discrimination against ethnic minorities in different markets. The pandemic brought a global recession and we know from past research that ethnic and racial gaps in labor market outcomes tend to increase during recessions (Hoynes et al., 2012). We also know that attitudes against ethnic minorities tend to be more hostile during tough times (Isaksen, 2019). Many studies around the world are reporting increased levels of xenophobia, not just against people of Asian descent but also against foreign people with other backgrounds (Elias et al., 2021). In fact, some studies suggest that there are historical linkages between epidemic threats and xenophobia (White, 2020). From the perspective of taste-based discrimination, this suggests that ethnic minorities would face increased labor market discrimination because of animosity during the pandemic.

We know that there were large differences between ethnic minorities and natives with respect to how Covid-19 affected people (Hansson et al., 2020). There are differences between ethnic minorities and natives with respect to the relative risk of contracting Covid-19 and differences in the resulting death rates. These can have important implications for ethnic minorities, including in, for example, the labor market. If employers know that immigrants face higher risks of contracting Covid-19, this may constitute a rational and statistical motivation for not hiring people from ethnic minorities. Statistical discrimination based on the higher risk of contracting Covid-19 may continue, even after the pandemic. Employers may then discriminate statistically against ethnic minorities because of fear of future epidemic outbreaks.

From both the taste-based and the statistical discrimination points of view, we have reasons to suspect that the pandemic might influence the magnitude of discrimination against ethnic minorities. One question is, however, whether there is any evidence of discrimination against ethnic minorities in the first place, before the Covid-19 pandemic. The answer is, yes.

There is ample of evidence of ethnic discrimination against various groups of minorities in the marketplace around the world prior to the Covid-19 pandemic. A large part of this evidence concerns labor and housing market discrimination against African Americans in the United States and against people with Arab-sounding names in European countries. For example, field experiments of labor market discrimination in Sweden consistently show that job applicants with Arab-sounding names, on average, need to apply for at least 50 percent more available jobs than job applicants with Swedish-sounding names in order to receive similar number of positive responses from employers (Carlsson & Rooth, 2007; Bursell, 2014; Aldén et al., 2021). Similar results exist for the Swedish housing market. Field experiments of housing market discrimination show that people with Arab-sounding names must apply for around twice as many available rental apartments than people with Swedish-sounding names in order to receive a similar number of offers to view an apartment from landlords (Ahmed & Hammarstedt, 2008; Ahmed et al., 2010; Carlsson & Eriksson, 2014).

Hence, there is indisputable evidence of ethnic discrimination in the marketplace prior to the Covid-19 pandemic. For reasons mentioned earlier, ethnic minorities may, however, have faced increased levels of discrimination against them in both the labor and housing markets during the pandemic because of increased levels of crisis-induced animosity and xenophobia and/or statistical inferences concerning how differently Covid-19 affected the minority and majority populations. In the next section, we give some evidence in support of our conjecture.

Evidence of Pandemic-Fueled Discrimination

Some empirical studies have investigated the ways in which the Covid-19 pandemic has influenced the scale of ethnic discrimination. We restrict ourselves to discussing studies that sought to test the direct (causal or quasi-causal) impact of Covid-19 on the magnitude of discrimination against ethnic minorities, either through controlled online and field experiments or by exploiting administrative data in the natural experimental setting provided by the pandemic. We begin by reviewing a study that in a general and controlled way established a causal relationship between the Covid-19 pandemic and harmful anti-social behavior. We then review some evidence on how the pandemic affected ethnic discrimination in the labor market. Finally, we discuss some findings related to Covid-19 and ethnic discrimination in the housing market.

Covid-19 and Harmful Behavior

Bartoš et al. (2021) investigated if stimulating the awareness of the pandemic increased hostility in the Czech Republic against foreigners from the European Union (EU), the United States, and Asia. In a general sense, this study established that crises like Covid-19 can indeed fuel harmful anti-social behavior and discrimination. The investigators conducted a web-based experimental study among a nationally representative sample of 2186 persons in terms of basic demographic characteristics in the Czech Republic during March 30–April 1, 2020. Participants made a series of anonymous decisions in a so-called help-and-harm task that combined elements of the well-known dictator game (Kahneman et al., 1986) and the joy of destruction game (Abbink & Sadrieh, 2009). The dictator game is a two-player game with a dictator and a recipient. The dictator is given an amount of money and an opportunity to share that money with the recipient who has received nothing. This simple game measures pure altruistic behavior of the dictator. The joy of destruction game is also a two-player game where both players are simultaneously given the same amount of money and the opportunity to destroy the other player’s money without fear of retaliation.

In the help-and-harm task, participants were instructed to raise, reduce, or do nothing to a predetermined amount of CZK 100 (about EUR 4) that would be given to people with different characteristics. The participants had to actively choose an amount between CZK 0 and 200. This simple experimental task is appealing because any allocation above CZK 100 could be interpreted as pro-social behavior (eliciting financial help) and any allocation below CZK 100 could be interpreted as anti-social behavior (eliciting financial harm). The participants’ allocation decisions had no monetary consequences for themselves, which means that selfish motives to harm others could be ruled out. Additionally, the recipient of the money had no strategic or reciprocal role in this situation other than simply receiving the money, which means that statistical discrimination can be ruled out as well so that any differential treatment must be due to taste-based discrimination. The participants made 17 money allocation decisions affecting recipients with various characteristics. In five of these cases, they allocated money to people who they knew were living in the Czech Republic, the EU, the United States, Asia, or Africa. The participants were informed that their decisions were consequential; that is, that some of their decisions would be randomly selected and implemented. They also knew that the decision makers were other people than the recipients.

Bartoš et al. (2021) then used the priming technique (Molden, 2014) to exogenously stimulate pandemic-related thoughts. Participants were randomized into a control group and a primed group. The primed group of participants answered a set of questions related to the Covid-19 pandemic before proceeding to the help-and-harm task. The pandemic-related questionnaire, which took about 13 minutes to complete, included questions about precautionary health behavior, social distancing, economic situation, and well-being. The questionnaire was designed to stimulate feelings and concerns related to the Covid-19 pandemic. The control group of participants answered the questionnaire after they had completed all their decisions in the help-and-harm task.

The results of this experiment showed that participants allocated less money to foreigners (people from the EU, the United States, Asia, and Africa) than to people from the Czech Republic. Overall, the participants displayed anti-social behavior against foreigners by allocating them CZK 92, less than the default amount of CZK 100, while they displayed pro-social behavior toward people from their own country by allocating them CZK 133. In the control group, participants allocated CZK 134 and CZK 94 to people from the Czech Republic and foreigners, respectively. In the primed group, participants allocated CZK 132 to people from the Czech Republic and CZK 89 to foreigners. Bartoš et al. (2021) concluded that priming participants with a questionnaire related to the Covid-19 pandemic significantly decreased the amounts allocated to foreigners but not to people from their own country. Moreover, the difference in the amounts received by foreigners and people from the Czech Republic was larger when participants were reminded about Covid-19 just before the help-and-harm task. From an economic perspective, these findings can be explained by taste-based discrimination, where favorable feelings toward your own group or derogatory feelings toward other groups may have generated the outcome of the experiment. The observations in this study are less connected with statistical discrimination since the experimental task did not involve any reciprocal motives or any strategic role of the recipients.

Covid-19 and Labor Market Discrimination

Two studies exploited the Covid-19 pandemic to analyze how the extent of discrimination is affected during a time of crisis in a natural experimental setting. The first study was conducted in Germany and examined the firing behavior of firms before and during the Covid-19 pandemic (Auer, 2022). The second study was based on data from the United States and compared business formation, ownership, and survival before and during the pandemic (Amuedo-Dorantes et al., 2021).

Auer (2022) examined discrimination against people with a migrant background in firing situations during the Covid-19 pandemic. He utilized repeated cross-sectional survey data on forced layoffs and short-time work. The data consisted of 17 waves of pandemic-related information about 11,440 people, representative for the German population in working age, between April and December 2020. Auer (2022) specifically exploited information about employment and demographic background included in these data in his study.

To examine the economic consequences of Covid-19, Auer (2022) restricted his analysis to people who had a job on March 1, 2020; in other words, just before firms started to lay off people because of the pandemic. His main outcome variable of interest was a dummy equal to 1 if respondents reported that they had been laid off since March, regardless of whether they had found another job after that, otherwise 0. Auer (2022) also used an alternative outcome variable, which was equal to 1 if respondents had been in any short-time work situation since March with provisionally reduced work time and pay (to facilitate employment and to avoid unemployment for workers), otherwise 0.

The main independent variable was a dummy equal to 1 if a respondent had a migrant background; that is, if the respondent or at least one of the respondent’s parents was born abroad. The data included detailed information about professional education as well as the industry and occupational position of each respondent. Furthermore, the data also included information about respondents’ household income, whether they felt under- or overqualified for their job, whether they had a full- or part-time job, and whether the job was temporary or permanent. All this additional information was used for adjustments in the regression analyses.

The data allowed Auer (2022) to examine whether people with migrant background suffered from firing discrimination during the pandemic; in other words, whether, compared to native Germans, they were more likely lose their jobs and less likely to be in a short-time work situation since March 2020, controlling for important factors such as industry, occupation, and time. Finally, Auer (2022) considered the heterogenous economic effects of the pandemic across different industries and months by using official administrative data on the cumulative monthly numbers of newly registered unemployed people in 2020 relative to 2019.

The results of Auer’s study showed that the probability of being laid off was 24 percentage points higher among people with a migrant background than among German natives if a firm’s industry- and month-specific unemployment rate increased by 100 percent in 2020 compared to 2019. In contrast, people with a migrant background were 19 percentage points less likely to be in a short-time work situation than native Germans during the same economic shock.

Auer (2022) concluded that firms were significantly more likely to keep native German employees than employees with a migrant background during the Covid-19 pandemic, inflicting further stress on them during a difficult time. He argued that the demonstrated firing discrimination was less likely to be an outcome of statistical inferences about worker productivity since little uncertainty should remain about the latter after they have been observed by employers in the workplace. Therefore, he concluded that firing discrimination is more likely to be a result of employer tastes and animosity against people with a migrant background.

Amuedo-Dorantes et al. (2021) studied discrimination against Asian immigrants in the United States during the Covid-19 pandemic by examining the dynamics of business formation, ownership, and survival. They examined the natural experiment represented by Covid-19 to investigate how discrimination against Asian immigrants may have influenced their self-employment rates. Amuedo-Dorantes et al. argued that an increase in the magnitude of discrimination against Asian immigrants during the Covid-19 pandemic was likely to be a result of a rise in animosity and hostile tastes because of the swift and surprising nature of the pandemic. Statistical inferences about the ability of a group of people are more likely to be based on long-term beliefs and observations rather than on a sudden shock.

Becker’s (1957) taste-based discrimination can stem from three actors in the labor market: employers, co-workers, and customers. Amuedo-Dorantes et al. (2021) focused on employer and customer discrimination. First, they hypothesized that employer discrimination against Asian immigrants may lead to higher unemployment among the latter and that it may encourage and push them into self-employment (Clark & Drinkwater, 2000). This may increase the extent of necessity entries of Asian immigrants into self-employment; that is, the transition from unemployment to self-employment, thus raising the business ownership rate among Asian immigrants (Fairlie & Fossen, 2020). Second, they hypothesized that customer discrimination against Asian immigrant business owners may reduce their sales (Borjas & Bronars, 1989), lower their self-employment rate, lower their business ownership rate, and decrease opportunity entries into self-employment; in other words, a transition from wage employment to self-employment (Fairlie & Fossen, 2020). Finally, they hypothesized that customer discrimination would be a stronger source of discrimination if a decrease in the business ownership rate is observed.

To test their hypotheses, Amuedo-Dorantes et al. (2021) used various data sources. Self-employment and demographic information were accessed from the monthly Current Population Survey for the period between January 2014 and November 2020. They used the longitudinal nature of this data to examine the dynamics of self-employment entries and exits. Furthermore, they collected coronavirus-related data on incidents and death rates from USAFacts database and on non-pharmaceutical interventions from the COVID-19 US State Policies database. The Asian group comprised immigrants while the comparison group consisted of non-Hispanic, native-born, white people.

Using a series of regression analyses, Amuedo-Dorantes et al. (2021) showed that the self-employment rate of Asian immigrants compared to that of non-Hispanic whites was significantly and negatively affected by the Covid-19 pandemic. Self-employment among Asian immigrants fell by 17 percent relative to that of non-Hispanic whites because of the pandemic. This result was robust to various specifications and controls. Remarkably, the magnitude of the pandemic-related decrease in the self-employment rate among Asian immigrants increased once industry controls were included. This means that the disparities between Asian immigrants and non-Hispanic white natives in business ownership could not be explained by industry segregation.

Amueo-Dorantes et al. (2021) found that the Covid-19 pandemic did not affect Asian immigrants and non-Hispanic whites differently with respect to entries into self-employment. However, when analyzing the necessity and opportunity entries separately, they found that Covid-19 tripled the necessity entries and decreased opportunity entries by 14 percent for Asian immigrants relative to those of non-Hispanic whites. Finally, they found that Covid-19 substantially affected the self-employment exit rates (i.e., transition from self-employment to some other labor-market status, e.g., unemployment or work employment) for Asian immigrants. Relative to non-Hispanic whites, the self-employment exit rate for Asian immigrants increased by more than 60 percent.

Hence, Amuedo-Dorantes et al. (2021) found evidence of increased exit rates, increased necessity entry rates, and decreased opportunity entry rates of self-employment among Asian immigrant people during the Covid-19 pandemic. Altogether, they concluded that their results support the hypotheses of both employer discrimination and customer discrimination. For two other studies on the employment effects of Covid-19 in the United States, see Borjas and Cassidy (2020) and Lee et al., (2021). Both studies indicate negative effects for ethnic groups. It is also in line with what another chapter in the present volume suggests (Bilgili et al., 2023, this volume).

In Sweden, however, the decline in total employment in 2020, the first year of the pandemic, was small, with only a slight decrease in total employment (see Andersson & Wadensjö, 2022a). Results from a register-based study also covering 2021 show a strong positive development of employment in Sweden among those born in Africa and Asia (see Andersson & Wadensjö, 2022b). It is a bit surprising that the employment of foreign-born employees increased, especially those born in Africa and Asia (the most positive development is found for those born in Afghanistan). One explanation may be that they work in sectors and occupations where the demand for labor increased during the pandemic. Another explanation could be the different ways in which the Covid-19 pandemic was managed in Sweden compared to most other countries. The results do not support the hypothesis that discrimination against foreign-born people increased during the pandemic in Sweden despite high segregation by industry.

Covid-19 and Housing Market Discrimination

One online thought experiment among participants from the United States (Lu et al., 2021) and one field experiment in the Belgian rental housing market (Verhaeghe & Ghekiere, 2021) suggest that the Covid-19 pandemic also may affect ethnic discrimination in the housing market. Lu et al. (2021) conducted an online vignette experiment to examine whether priming Covid-19 salience increased discrimination against Asians and Hispanics in the United States. Specifically, they examined whether making participants temporarily think about how Covid-19 affected their lives had any impact on the magnitude of discrimination against hypothetical roommates from different backgrounds. They conducted the study in August 2020 among a nationally representative sample of 5000 American adults. In the vignette experiment, they asked participants to imagine that they were looking for a roommate and that, for this purpose, they had posted an advertisement about room availability on a popular online housing platform. The participants were then given a supposed e-mail response from a prospective roommate. The ethnicity of this prospective roommate was randomly varied by assigning a name with a distinctive ethnic connotation: white, black, Hispanic, East Asian, or South Asian. After the hypothetical case, the participants answered two questions that elicited how likely they thought it would be that they would contact the prospective roommate in that situation. Another four questions measured the participants’ views about the hypothetical roommate related to responsibility, courteousness, financial stability, and cultural compatibility. In other words, the first set of questions measured discriminatory intent while the second measured both prejudices and stereotypical beliefs.

The participants were randomly assigned to a control group or a primed group. For the primed group, the online survey started with some current information and a battery of questions about the Covid-19 pandemic, priming Covid-19 salience before they made the hypothetical roommate experiment. For the control group, the online survey started with the experimental part and ended with the Covid-19 pandemic information and questions.

The findings of Lu et al. (2021) showed that priming Covid-19 pandemic salience increased not just the discriminatory intent but also the prejudices and stereotypes against hypothetical Asian and Hispanic roommates. For example, their results indicated that participants in the primed group were 7, 4, and 6 percentage points more likely than participants in the control group to report that they were strongly disinclined to reply to a hypothetical Hispanic, South Asian, and East Asian prospective roommate, respectively. In contrast to the studies discussed earlier, this study also provides some evidence of increased statistical discrimination. For example, participants in the primed group were more likely than participants in the control group to believe that both East Asian and South Asian people are extremely irresponsible and that Hispanic and South Asian people are financially unstable. Actions based on both these beliefs would constitute statistical discrimination.

Verhaeghe and Ghekiere (2021) conducted a field experiment in the housing market in a metropolitan city in Belgium. They sent out 500 matched inquiries before the outbreak and another 500 after the outbreak of Covid-19 to landlords with available rental apartments. In the inquiries, the fictitious tenants asked landlords whether they could visit the available dwelling. The fictitious inquiries were sent through e-mails and tenant ethnicity was signaled though distinctive ethnic names: Belgian-, Congolese-, and Maghrebian-sounding names. One of the matched pair of tenants always had a Belgian-sounding name while the name for the other tenant was randomly Congolese- or Maghrebian-sounding. Verhaeghe and Ghekiere then examined whether applicants of Maghrebian and Congolese origin were discriminated against in comparison to applicants with Belgian origin with respect to landlord positive response rates. They found that the relative net discrimination against Maghrebian applicants increased during the pandemic from 20 to 36 percent. However, they also found that the net rate of discrimination against Congolese candidates decreased from 17 to 6 percent. They provided a few cautious explanations to their mixed findings. One important explanation is that the Congolese minority in Belgium relative to the Maghrebian one is a lot smaller and, therefore, constitutes less of a threat or perceived competition among predominantly Belgian landlords. Another explanation is that the media in Belgium highlighted the potential higher occurrence of Covid-19 among Maghrebian and Turkish people. They, therefore, suggest that the effect of the pandemic on the magnitude of discrimination varied across different immigrant groups depending on specific circumstances.

Discussion and Policy Recommendations

Covid-19 affected everybody. At first, it was argued that the pandemic, to some extent, would be an equalizer that could reduce inequalities in society since it randomly affected both rich and poor, young and old, men and women, as well as natives and foreigners. We know that this was not actually the case. For example, Covid-19 has, without a doubt, been deadliest for the senior population. We also know that people with lower earnings on average were affected more negatively by Covid-19 and that ethnicity is important to consider, since ethnic minorities are usually overrepresented in lower-income occupations. Some ethnic minorities were also more likely to have occupations in job sectors where they were less likely to be able to work from home. Hence, the origin of Covid-19 was a medical matter, but its scope was societal.

Covid-19 struck ethnic minorities a lot harder than natives. Consider the case of Sweden. According to a report from the Public Health Agency in Sweden, some foreign-born groups had a higher risk of being infected with the virus than the Swedish-born population during the period between March 2020 and February 2021, measured as the number of confirmed cases (Public Health Agency in Sweden, 2021). More importantly, almost all foreign-born groups faced a higher risk of ending up in intensive care units than Swedish-born people. For example, people born in Africa or in the Middle East were five times more likely to need intensive care than people born in Sweden. The relative risk of dying because of Covid-19 was also higher for people born abroad in comparison to those born in Sweden. People born in Africa and in the Middle East, for example, were at three times greater risk of dying from Covid-19 than Swedish-born people. These are considerable differences and clearly show that the pandemic affected ethnic minorities differently. Similar observations are also made in other countries. Note, however, that mortality rates for diagnoses other than Covid-19 was lower for ethnic minorities (measured by country of birth) compared to native Swedes according to a study using logistic regressions (see Drefahl et al., 2020). Excess mortality may be a better measure for comparing the development of mortality across ethnic and native individuals.

Similar findings are documented by examining excess mortality in Sweden among people born in different parts of the world during a three-month period (March–May 2020) of the pandemic (Hansson et al., 2020). It shows that people born in Somalia, Syria, and Iraq had significantly higher excess mortality rates than Swedish-born people. For example, excess mortality during the period in focus, compared to 2016–2019, among middle-aged (40–46 years old) people born in Somalia, Syria, and Iraq was about 220 percent. The corresponding percentage for middle-aged people born in Sweden, the EU, the Nordic countries, or North America was minus 1 percent.

Hansson et al. (2020) provide an explanation of why there are large differences between ethnic minority groups and natives in how Covid-19 affected them. They argue that segregation is an important contributor. Ethnic minorities are overrepresented in densely populated areas and the number of people living in a household is higher among ethnic minorities than among natives. Moreover, it is more common among ethnic minorities that relatives take care of their elderly than among natives. Longer commuting distances and dependence on the public transport are other factors affecting the relative risk of contracting Covid-19. Hence, a number of aspects that originate in lower socioeconomic status, segregation, and past discrimination, may, in different ways, explain why Covid-19 affected various vulnerable populations. Thus, strategies adopted to combat Covid-19 were often criticized for being designed with respect to a homogeneous majority society without considering existing inequalities among people (Hansson & Jakobsson, 2020). From a sociological perspective, this could constitute a form of ‘institutional’ or ‘structural’ discrimination (Small & Pager, 2020). The idea behind these concepts is that something other than discriminating individuals (as in economic theories of discrimination) is responsible for ethnic or racial disparities in society.

The high incidence of Covid-19 among the foreign born in Sweden is not combined with a negative development in the labor market. On the contrary, the employment development was more positive among the foreign born than among those born in Sweden. However, the foreign born still have a lower employment rate than the Swedish-born and discrimination may be a factor behind this difference.

One group facing a difficult situation in the labor market is unaccompanied minors (see, e.g., Çelikaksoy & Wadensjö, 2017). There are large differences among those belonging to this group: those arriving at a younger age, boys, those living in the Stockholm area, and those coming from Afghanistan are employed to a higher extent than other unaccompanied minors. It is important to follow what happened with this group during the pandemic years. Additionally, it is also important to follow the development of the many unaccompanied minors who arrived from Ukraine in 2022 following the Russian invasion.

In this chapter, we have concentrated on analyzing the effects of the Covid-19 pandemic on discrimination against ethnic minorities. However, we must remember that there are also other vulnerable groups of people in society that, much like ethnic minorities, may have faced increased levels of discriminations during the Covid-19 pandemic. We know, for example, from field experimental studies that people are discriminated against because of their age (Ahmed et al., 2012; Carlsson & Eriksson, 2019), disability (Ameri et al., 2018; Bjørnshagen & Ugreninov, 2021), sexual orientation (Weichselbaumer, 2003; Ahmed et al., 2013), and gender identity (Granberg et al., 2020; Ahmed et al., 2021) in the labor market. Indeed, several scholars highlight the potential risks of amplified disadvantages of the elderly (Shakespeare et al., 2021), LGBT people (Mattei et al., 2021), and disabled people (Swift & Chasteen, 2021) during a crisis like Covid-19.

The policy implications may differ between countries. Some countries may have had increased discrimination against ethnic groups during the pandemic, others not. Hence, it is important for further research to investigate the effects of Covid-19 on labor market discrimination and segregation.