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Economic well-being and anti-Semitic, xenophobic, and racist attitudes in Germany

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Abstract

The fear and hatred of others who are different has economic consequences because such feelings are likely to translate into discrimination in labor, credit, housing, and other markets. The implications range from earnings inequality to intergenerational mobility. Using German data from 1996 and 2006, we analyze the determinants of racist and xenophobic feelings towards foreigners in general, and against specific groups such as Italians, Turks, and Asylum Seekers. We also analyze racist and anti-Semitic feelings towards German citizens who differ in ethnicity (Aussiedler from Eastern Europe) or in religion (German Jews). Individuals’ perceived (or actual) economic well-being is negatively related to the strength of these feelings. Education, and having contact with foreigners mitigate racist, anti-Semitic and xenophobic feelings. People who live in states which had provided above-median support of the Nazi party in the 1928 elections have stronger anti-Semitic feelings today. The results are not gender-driven. They are not an artifact of economic conditions triggering feelings about job priority for German males, and they are not fully driven by fears about foreigners taking away jobs. The results of the paper are consistent with the model of Glaeser (Q J Econ 120(1):45–86, 2005) on hate, and with that of Akerlof and Kranton (Q J Econ 105(3):715–753, 2000; J Econ Perspect 19(1):9–32, 2005) on identity in the utility function.

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Notes

  1. However, their explanatory variables include only age, gender, education, marital status and labor force status and the question asked in the 1988 that defined ant-immigrant attitude is completely different from those in the 2003 and 2008 surveys.

  2. Relatedly, Mayda and Rodrik (2005) analyze why some people favor protectionist trade policies while others are pro-trade. They find that pro-trade preferences are correlated with individuals’ human capital and relative economic status.

  3. Applications of this concept include Humlum et al. (2012) and Antecol and Cobb-Clark (2008).

  4. As detailed later, support of the Nazi Party in 1928 is not correlated with the level of development in those areas today; that is, areas that produced more votes for the anti-Semitic Nazi platform in 1928 are not systematically different from other areas today in terms of economic development or level of income.

  5. Although it is not expected for a Jewish person to have a distaste for other Jews, or an ethnic German (Aussiedler) to have a distaste for ethnic Germans, there is no reason to rule out the possibility that a Jewish person or an ethnic German may have a negative feelings for other minority groups. Therefore, the sample we use in the regressions include German citizens who are Jewish, and those who are ethnic minorities.

  6. (German Federal Ministry of the Interiors web site, accessed on Dec 28, 2013: http://www.bmi.bund.de/DE/Themen/Gesellschaft-Verfassung/Staatliche-Ordnung/Wahlrecht/Auslaenderwahlrecht/auslaenderwahlrecht_node.html).

  7. There is, in fact, a different question in ALLBUS that asks whether foreigners living in Germany should have the right to vote in municipal elections, which we did not use in the paper.

  8. Sometimes a distinction is made between Aussiedler and Spätaussiedler (“Late Aussiedler”), depending on how soon after World War II the individuals came to present-day Germany. We make no such distinction and refer to all such individuals as “Aussiedler” or “ethnic Germans from Eastern Europe”.

  9. There are about 102,000 Jews in Germany, which is 0.13 % of the 80 million population (http://de.statista.com/statistik/daten/studie/1232/umfrage/anzahl-der-juden-in-deutschland-seit-dem-jahr-2003/).

  10. The reason for the geographic differences in religious denomination are largely rooted in history. After the Protestant Reformation in the 1500s, the rulers of the different territories of the Holy Roman Empire either chose to follow the Reformation or to remain Catholic. Areas where the rulers of that time chose to follow the Reformation are still largely protestant, and the predominantly Catholic areas today tended to have rulers that chose to remain Catholic.

  11. The states are Schleswig–Holstein, Hamburg, Niedersachsen, Bremen, Nordrhein-Westfalen, Hessen, Rheinland-Pfalz, Baden-Württemberg, Bayern, Saarland, Berlin, Brandenburg, Mecklenburg-Vorpommern, Sachsen, Sachsen-Anhalt, and Thüringen.

  12. Because each state contributes only two observations, there is not much within-state variation in the data, and dropping these variables had no impact on other coefficients.

  13. Dustmann, Fabbri and Preston (2011) also find that higher education is associated with lower prejudice.

  14. In the interest of space, we only report the models with indices as dependent variables.

  15. The models that include perceptions on both personal economic well-being and national economic conditions provided very similar results although in some cases the precision of the estimated coefficients were reduced. These results are reported in Appendix Table 19.

  16. It is interesting to note that the coefficient of “Percent Foreign” is consistently positive and it is statistically significant in most models (nor reported in tables to conserve space), indicating the positive association between the proportion of foreigners in a state and the extent of negative feelings. Nevertheless, as shown in Tables 7, 8, 9, holding constant percent foreigners in the state, personal contact with foreigners reduces these negative feelings.

  17. They also show that anti-Semitism is stronger among the cohort that grew up under the Nazi regime and that different zones of Germany, occupied by different countries after the WW II, exhibit different patterns of anti-Semitism.

  18. This question was asked in converse as “It is actually good for a child if the mother is working in the market instead of just concentrating on the household.” For consistency with other questions, we reversed the question and the answers.

  19. This point is also made by Voigtlaender and Voth (2012b).

  20. It is predicted that 55 % of the U.S. population will consist of African-Americans and those with Hispanic or Asian descent (U.S. Census Bureau). Populations of the EU countries are becoming more heterogeneous as well. A visible example of the inflow of foreigners and increased prevalence of second-generation immigrants in Europe can be seen in the soccer industry. In 1990, the prominent German soccer team Bayern Munich had three players on its 22-player roster who were not German (13.6 % of the roster). In 2013, almost half of the Bayern roster (46 %) consisted of foreign players. The same is true for any other soccer team in Europe. For example, the share of foreign players rose from 19 % in 1990 to 33 % in 2013 for the prominent Spanish soccer team Barcelona. The picture is even more striking regarding the national soccer teams. A player must have citizenship of that country to be eligible to play on the national team. In 1990, the French national soccer team had two black French players (14 % of 25 players). In 2013 the same team includes 9 black players (41 % of 22 players). German national soccer team had no player who was not of German descent in 1990. The team has 8 players in 2013 that have a migration background.

  21. Interestingly, research exists to show that life satisfaction of natives is higher in locations with higher concentration of immigrants (Akay et al. 2014).

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Acknowledgments

We thank Luiza Pogorelova and Bahadir Dursun for research assistance. Anna Piil Damm, Marianne Simonsen, Alex Koch, Leyla Mocan, Carmine Guerriero, James Garand, and seminar participants at Aarhus University, Galatasaray University, LSU, and the 2014 European Association of Law and Economics Conference in Aix-En-Provence, and especially two anonymous referees provided helpful comments.

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Authors and Affiliations

  1. Louisiana State University, Baton Rouge, LA, USA

    Naci Mocan

  2. NBER, Cambridge, MA, USA

    Naci Mocan

  3. IZA, Bonn, Germany

    Naci Mocan & Christian Raschke

  4. Sam Houston State University, Huntsville, TX, USA

    Christian Raschke

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  1. Naci Mocan
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Correspondence to Naci Mocan.

Appendix

Appendix

See Tables 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25.

Table 15 The impact of perceived personal economic conditions on racism, xenophobia, and anti-Semitism: models with age group dummies
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Table 16 The impact of perceived National Economic Conditions on racist attitudes
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Table 17 The impact of perceived National Economic Conditions on xenophobic attitudes
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Table 18 The impact of perceived National Economic Conditions on anti-Semitic attitudes
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Table 19 The impact of perceive personal economic conditions and national economic conditions on racist, anti-Semitic, and xenophobia attitudes
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Table 20 The impact of perceived personal economic conditions on racism: detailed employment classifications
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Table 21 The impact of perceived personal economic conditions on xenophobia: detailed employment classifications
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Table 22 The impact of perceived personal economic conditions on anti-Semitism: detailed employment classifications
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Table 23 Descriptive statistics by gender
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Table 24 Gender specific estimation results
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Table 25 The impact of perceived personal economic conditions on racism, xenophobia, and anti-Semitism—control for kick out foreigners when jobs get scarce
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Mocan, N., Raschke, C. Economic well-being and anti-Semitic, xenophobic, and racist attitudes in Germany. Eur J Law Econ 41, 1–63 (2016). https://doi.org/10.1007/s10657-015-9521-0

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