Facing the challenges of discrimination and migrant integration
Facing the challenges of discrimination and migrant integration
Economic research suggests that migration is beneficial to both the receiving and sending countries – if borders were more open, the world’s economic output could approximately double (Alesina et al., 2016; Clemens, 2011; Economist, 2019). However, “often [migrants] live and work in the shadows, denied their rights and are vulnerable to discrimination, exploitation and marginalization” (FRA Director O’Flaherty, 2017); specifically, previous research finds substantial evidence of discrimina-tion against foreigners and minorities in various areas, including criminal justice, education, business, housing, health care, media, and politics (see, e.g., Enos (2016), Marit Rehavi & Starr (2014), Rich (2014), and Zschirnt & Ruedin (2016)). As a result, many migrants are not adequately integrated; hence, to prevent discrimination and foster migrant integration, there is need for improved social co-hesion, social inclusion, and acceptance of multiculturalism (OECD Secretary-General Gurría, 2016).
Many significant political developments of the past decade (e.g., the election of Donald Trump, the rise of populism in Europe and the Brexit referendum) can to some extent be attributed to fear of mass migration (Economist, 2019). Admittedly, there are some reasonable concerns regarding immigration that should not be neglected; however, in general, the fears of mass migration and their potential negative consequences are unfounded or severely exaggerated (e.g., Card (2005)). For instance, in OECD countries, people tend to vastly overestimate how many migrants exist, how much migrants cost, and how much they benefit from access to social benefit programs (Alesina et al., 2018b, 2018a). Likewise, half of Europeans think that migrants are going to take their jobs and/or exploit social welfare services. Despite of actual migrant numbers, around half of the public in the USA and among the OECD’s European members suggest ‘‘it’s too many” – migration is too often seen as a threat and not as an opportunity (Gurría, 2016).
Moreover, anti-migrant attitudes have been fueled worldwide by the Covid-19 pandemic (Bartos et al., 2020) and an increased usage of automated pre-screening tools in employee-selection procedures further diminishes migrants’ labor market prospects due to “algorithmic discrimination” (e.g., European Commission, 2021; Orwat, 2020). These trends in discrimination against migrants are espe-cially worrisome when considering the worldwide progression of population aging, because many (in-dustrialized) countries are planning to rely on migrants to mitigate problems linked to future worker shortage (e.g., Kadkoy & Sak, 2019). As an example, the German population is both shrinking and aging. While immigration will not be able stop the demographic change, it can slow it down to some extent. Consequently, many economists argue that Germany needs to increase its attempts at attract-ing migrants (e.g., Gathmann et al. (2014)) ).
Successful migrant integration is a multidimensional concept, in the implementation of which societies as well as countries and their institutions all play a central role. While the open-mindedness toward migrants is primarily shaped by the population, it is the responsibility of both the sending and receiving countries and their institutions to create a legal framework that enables swift and easy integration.
How can we appropriately address the challenges of discrimination and migrant integration?
Examples for specific challenges of discrimination and migrant integration
Many economies are undergoing a demographic shift toward older societies, which is likely be accom-panied with a slowdown in economic growth. Attracting younger migrants is crucial for mitigating the negative consequences linked to population aging, but newly arrived immigrants tend to be less edu-cated and skilled than the local population. Hence, there is a need for skill development in advance of migrating. However, aging economies require low- and high-skilled workers; in any case, economies need a labor force with diversified abilities. Existing practices of skills development have been of small scale and limited to selective policies. As an example for programs designed for skill development, the German government is training young people in Vietnam in both nursing and the German language. However, such examples are scarce. What can we learn from this pilot project? How can we improve programs for education and skill development of migrants?
Policymakers tend to neglect the specific needs of female migrants. To give some examples, from the start of their careers, female migrants are at a higher risk of being excluded from the labor market for a variety of reasons, including their, on average, higher number of children. Similarly, they are more likely than native-born women to be in long-term unemployment, involuntary idleness, and not in em-ployment, formal education or training (NEET) as young adults. These specific challenges emphasize the necessity for a gendered approach – how can we improve the situation for female migrants?
The Australian migration system has attracted large international prominence. What can we learn from other countries’ migration and integration policies, such as, e.g., Australia’s point-based system? (For details, see, e.g., Economist (2019) and Papademetriou & Sumption (2011)).
When considering alternative ways to control migration flows, one previously suggested option is let-ting migrants have to pay a price to migrate. As an example, Nobel Laureate Gary Becker (2011) sug-gests auctions; the money could then be used for, e.g., investing in the public pension and health care system (see, e.g., Zavodny (2015) for further information). A somewhat more controversial option is proposed by Posner and Weyl (2018) – what if each citizen could sponsor one migrant from a poor country, and be entitled to a share of her income? This would create a direct personal connection between migrants and locals. The migrants would be free to leave and return to their home countries, but not to disappear and work in the black market. Such a system would require strict laws against hiring illegal workers. How can we improve existing migration-flow mechanisms and what are promis-ing alternatives?
The findings provided by Alesina et al. (2018b, 2018a) suggest that salience and narratives are more effective in debiasing attitudes toward immigration than official statistics. How can we use these find-ings to mitigate prejudice and discrimination? As an example, which role does the media play in shap-ing people’s views on discrimination, multiculturalism and migrant integration?
With respect to social cohesion and social inclusion, we have to acknowledge that migrants often do not stay permanently, e.g., migrant seasonal workers. Hence, an optimal integration policy cannot equal cultural assimilation. Cultural diversity is a strength that also pays off economically in the long run. Similar to migrants who only stay for limited periods of time, those who stay permanently do not have to give up their cultural ties to their home country, but they should open up to the culture of the host country. How can we harmoniously combine efforts to successfully integrate migrants and foster multiculturalism?
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Alesina, A., Miano, A., & Stantcheva, S. (2018a). Immigration and Redistribution. NBER Workin Paper Series, 24733. http://www.nber.org/papers/w24733
Bartos, V., Bauer, M., Cahlikova, J., & Chytilová, J. (2020). COVID-19 Crisis Fuels Hostility against Foreigners. CESifo Working Paper Series, 8309(June).
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Clemens, M. A. (2011). Economics and emigration: Trillion-dollar bills on the sidewalk? Journal of Economic Perspectives, 25(3), 83–106.
Enos, R. D. (2016). What the Demolition of Public Housing Teaches Us about the Impact of Racial Threat on Political Behavior. American Journal of Political Science, 60(1), 123–142.
European Commission. (2021). Algorithmic discrimination in Europe. https://op.europa.eu/de/publication-detail/-/publication/082f1dbc-821d-11eb-9ac9-01aa75ed71a1
Gathmann, C., Keller, N., Monscheuer, O., Straubhaar, T., Schäfer, H., Zimmermann, K. F., & Brücker, H. (2014). Zuwanderung nach Deutschland-Problem und Chance für den Arbeitsmarkt. Wirtschaftsdienst, 94(3), 159– 179. https://www.wirtschaftsdienst.eu/inhalt/jahr/2014/heft/3/beitrag/zuwanderung-nach-deutschland-problem-und-chance-fuer-den-arbeitsmarkt.html
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Kadkoy, O., & Sak, G. (2019). Role of G20 in Designing Immigration Policies to Support Population Aging. https://www.g20-insights.org/policy_briefs/role-of-g20-in-designing-immigration-policies-to-support-population-aging/
Marit Rehavi, M., & Starr, S. B. (2014). Racial disparity in federal criminal sentences. Journal of Political Economy, 122(6), 1320–1354.
O’Flaherty, M. (2017). Facing the challenges of migrant integration. https://fra.europa.eu/en/news/2017/facing-challenges-migrant-integration
Orwat, C. (2020). Risks of Discrimination through the Use of Algorithms. German Federal Anti-Discrimination Agency. https://www.antidiskriminierungsstelle.de/EN/homepage/_documents/
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Rich, J. (2014). What Do Field Experiments of Discrimination in Markets Tell Us? A Meta Analysis of Studies Conducted since 2000. IZA Discussion Paper, (8584).
Zavodny, M. (2015). Should countries auction immigrant visas? IZA World of Labor, (November), 1–10. https://wol.iza.org/articles/should-countries-auction-immigrant-visas/long
Zschirnt, E., & Ruedin, D. (2016). Ethnic discrimination in hiring decisions: a meta-analysis of correspondence tests 1990–2015. Journal of Ethnic and Migration Studies, 42(7), 1115–1134.
Steffen Müller ist Wissenschaftlicher Mitarbeiter und Doktorand am Lehrstuhl für Wirtschaftspolitik an der Universität Hamburg. Während seines Studiums in Quantitative Finance und Economics (M.Sc.) an der Christian-Albrechts-Universität zu Kiel, arbeitete er als Hilfswissenschaftlicher Mitarbeiter am Institut für Weltwirtschaft (IfW). Neben seinem Interesse für statistische Modellierung und Prognosen untersucht er im Rahmen seiner aktuellen Forschungsprojekte: Die Auswirkungen von konsumentenbasierter Diskriminierung in professionellen Sportmärkten, den Einfluss von Alters- und Generationseffekten in direktdemokratischen Wahlentscheidungen, sowie Möglichkeiten zur Nutzung neurophysiologischer Daten in der Analyse von Entscheidungsprozessen mit Hilfe von Methoden maschinellen Lernens. Seine primären Forschungsschwerpunkte liegen in den Bereichen Politische Ökonomie, Verhaltensökonomie und Sportökonomie. Darüber hinaus ist er Beiratsmitglied im Hanseatischen Börsenkreis (HBK) der Universität Hamburg E.V.