Homeownership is often treated as a marker of successful integration. Governments track it, linking it to wealth accumulation and social stability, and the population cares about it. Yet across Europe, immigrants and their children can encounter very different housing trajectories. Where people live, whether they gain access to homeownership, and how often they move are closely linked to broader outcomes such as social participation, educational opportunity, and labour market success (Borjas, 2002)

Research in this area has long been shaped by spatial assimilation (Alba and Logan, 1992), which views residential mobility and housing upgrading as key mechanisms through which immigrants integrate into host societies. From this perspective, inequalities in housing outcomes (i.e. differences between immigrants and natives) should gradually diminish for immigrants who settle and for their descendants. Yet a growing body of evidence points to more uneven trajectories. Approaches emphasising stratification and segmented assimilation suggest that structural barriers – including discrimination, labour market segmentation, and institutional constraints in housing systems – may limit residential mobility and access to homeownership, even over time and across generations (Zhou, 1997).

Housing systems also differ across countries. There are distinct differences in access to credit across contexts that can perpetuate differences between immigrants and majority populations. Likewise in the rental sector, where different levels of social housing availability and tenancy protection may make renting more economically feasible as an alternative to owner-occupied tenure (Kemeny, 2006; Mulder and Billari, 2010). Despite extensive research on immigrant housing within individual countries, comparative evidence remains scarce. This is partly due to challenges of data comparability across national contexts. Moreover, much less is known about how housing and residential outcomes evolve between the first and second generation, and to what extent these processes depend on national housing systems.

To address these gaps, in a recent article (Harrison et al. 2026), we harmonised panel and administrative data across five European countries. We focused on two outcomes: first, residential relocation, to capture whether individuals change dwelling, a factor that reflects opportunity, constraint, and the overall fluidity of housing markets; second, housing tenure, with particular attention to moves into homeownership versus remaining in rental housing. Tenure transitions are not only markers of socioeconomic position, but also reflect institutional barriers, credit access, and differences in the value placed on homeownership across groups and contexts.

Residential mobility: convergence and constraint

Turning first to residential mobility (Figure 1), the most striking finding is the scale of cross-national variation. Residential moves are considerably more common in Switzerland, France, and Sweden than in the UK and Germany, reflecting well-established differences in housing market structure and regulation. These national patterns shape residential opportunities for immigrants and natives alike.

Within countries, however, mobility varies substantially across origin groups. Immigrants are not uniformly more or less mobile than natives. In the UK, for example, immigrants from European and Western countries and from India move more frequently than natives, while those from Pakistan move less. Sweden stands out for particularly high mobility among immigrants from the Middle East. By contrast, individuals of Turkish origin consistently display lower mobility across all five countries.

Across generations, there is little evidence of a single or linear assimilation trajectory. In both the UK and France, second-generation groups tend to be less mobile than both first-generation immigrants and natives, suggesting residential stabilisation rather than upward mobility. Germany shows the opposite pattern: descendants of immigrants are more mobile than their parents, and in some cases even more mobile than native Germans. In Sweden and Switzerland, generational differences are smaller, though some Eastern European groups become more mobile in the second generation. Overall, residential mobility does not steadily converge across generations, but instead reflects a complex interaction between origin, generation, and national context.

Housing tenure and intergenerational change

Figure 2 shifts attention from whether people move to where they move within the housing system. Again, national housing regimes play a decisive role. Transitions into homeownership are rare in Germany, but relatively common in France and especially Sweden, among both immigrants and natives.

Across all countries, immigrants are generally less likely than natives to move into homeownership and more likely to enter rental housing, including social housing where it exists. These gaps are particularly pronounced for non-Western groups in France and Sweden.

The second generation shows clearer signs of progress. Descendants of immigrants are more likely than the first generation to transition into homeownership, reflecting both life-course timing and adaptation to host-country housing norms, a process reinforced by rising levels of partnership exogamy. However, convergence with natives remains limited. Only descendants of European and some Asian origins reach homeownership at similar rates to natives. Most non-Western groups continue to face disadvantages and remain overrepresented in rental and social housing, particularly in France.

Take-home messages

Three conclusions stand out. First, destination context matters. Differences in housing systems shape outcomes for immigrants and natives alike. In countries with highly regulated rental markets and limited pathways from renting to owning, such as France, disadvantages in tenure tend to persist across generations. By contrast, systems that combine affordable rental options with easier access to credit are associated with greater residential mobility and higher rates of transition into homeownership.

Second, intergenerational improvement is real but uneven. While the descendants of immigrants often fare better than their parents, convergence with native populations is far from guaranteed, particularly for non-Western groups.

Finally, housing institutions play a critical role in shaping long-term integration. This could inspire policy implications which focus on the removal of barriers to credit access and address discrimination in housing markets, both of which may have lasting effects, not only for immigrants themselves, but also for their descendants. Otherwise, inequality can be reproduced across generations despite educational and labour market improvements. 

By placing immigrant housing outcomes in a comparative perspective, this research highlights integration as a context-dependent and multi-generational process. Future work combining quantitative comparisons with qualitative insights into housing preferences, discrimination, and decision-making would further illuminate the mechanisms behind these patterns.

References

Alba, R. D. and Logan, J. R. (1992) ‘Assimilation and stratification in the homeownership patterns of racial and ethnic groups.’, International Migration Review, 26(4). doi: 10.1177/019791839202600411.

Borjas, G. J. (2002) ‘Homeownership in the immigrant population’, Journal of Urban Economics, 52(3), pp. 448–476. doi: 10.1016/S0094-1190(02)00529-6.

Harrison, J., Delaporte, I., Kulu, H. et al. (2026) Residential Mobility and Housing Tenure Among Immigrants and Their Descendants: a Cross-National Analysis of Five European Countries. European Journal of Population, 42(2). https://doi.org/10.1007/s10680-025-09757-3.

Kemeny, J. (2006) ‘Corporatism and housing regimes’, Housing, Theory and Society, 23(1), pp. 1–18. doi: 10.1080/14036090500375423.

Mulder, C. H. and Billari, F. C. (2010) ‘Homeownership regimes and low fertility’, Housing Studies, 25(4), pp. 527–541. doi: 10.1080/02673031003711469.

Zhou, M. (1997) ‘Segmented assimilation: Issues, controversies, and recent research on the new second generation’, International Migration Review, 31(4), pp. 975–1008. doi: 10.2307/2547421.

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America is struggling with continuing its birthright citizenship, which was established by the 14th Amendment to the US Constitution in 1868. Section 1 of the 14th Amendment declares: “All persons born or naturalized in the United States, and subject to the jurisdiction thereof, are citizens of the United States and of the State wherein they reside”. 

The struggle

Shortly after taking office on 20 January, President Trump issued an executive order restricting birthright citizenship, insisting that the 14th Amendment does not apply to the births of unauthorized migrants. Many have raised objections, pointing out that America has upheld birthright citizenship for more than 150 years and as US laws apply to unauthorized migrants, so the Constitution’s 14th Amendment should apply to them too.

The American Civil Liberties Union and several states have filed federal legal challenges to Trump’s executive order restricting birthright citizenship. The American Bar Association described it as an attack on a “constitutionally protected” right. Also, no less than four federal judges and a growing number of courts have blocked the order. How the US Supreme Court, where conservative justices form a supermajority, would interpret the 14th Amendment is not clear. The litigation over Trump’s executive order is likely to focus on what it means for someone to be “subject to the jurisdiction” of the United States.

Shortly after becoming president on January 20, Trump falsely claimed that “We are the only country in the world that does this with the birthright, as you know, and it’s just absolutely ridiculous.” Actually, at least 33 countries provide automatic citizenship to anyone born within their borders. Those countries, located mostly in the Western hemisphere, include America’s neighboring countries of Canada and Mexico.

Foreign-born population

The number and proportion of foreign-born residents in America have varied considerably over the past several centuries (Table 1). In 1890, for example, they totaled nearly ten million and their proportion reached a high of 14.8%. Following World War II, their number declined to below 10 million and their proportion fell to a record low of 4.7% in 1970. The early 21st century saw a marked increase and their number rose to 31 million (11% of the total population). In 2024, the estimated 51.6 million foreign-born residents accounted for a record-breaking 15.6% of America’s population.

Births to foreign-born mothers

Over the period 2014-2024, the average number of births to foreign-born mothers in the US was 850,000, varying from a high of 910,000 in 2016 to a low of 780,000 in 2021. Their share of total births remained relatively stable at approximately 23% (Table 2) – greater than the proportion of foreign-born population in the same period (about 14%).

The exact number of births to unauthorized foreign-born mothers is unknown. However, with a few reasonable assumptions (detailed in the footnotes to Table 2), an annual average total of around 213,000 can be estimated over the period, possibly ranging between 180,000 births in 2021 and a high of 245,000 in 2016.  

Those annual estimates also provide an indication of the distribution of births among native-born and foreign-born mothers. Over the past 11-year period, approximately 77% of the births in America were to native-born women and 23% were to foreign-born mothers, 17% to authorized foreign-born mothers and 6% to unauthorized foreign-born mothers (Figure 1).

Conclusions

As a result of President Trump’s recent executive order, birthright citizenship has developed into a major political and legal struggle for America. The outcome of that struggle is now playing out in US courts. While the legal outcome is currently uncertain, its major demographic consequence is already clear. 

If birthright citizenship is restricted, as President Trump has ordered, up to 225,000 children born to unauthorized foreign-born mothers each year – around 6% of America’s annual births – will not be granted US citizenship. 

References

American Civil Liberties Union (2025) “Immigrants’ Rights Advocates Sue Trump Administration Over Birthright Citizenship Executive Order”. January 20, ACLU, Washington, D.C.

Baker, Bryan and Robert Warren (2024) “Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2018-January 2022”. April, US Office of Homeland Statistics, Washington, D.C. 

Bay, William (2025) “The ABA supports the rule of law”. February 10, American Bar Association (ABA), Chicago, Illinois.

Camarota, Steven and Karen Zeigler  (2021) “Fertility Among Immigrants and Native-Born Americans”. February 16, Center for Immigration Studies, Washington, D.C.

Hussein, Mohamed A. (2025) “Which countries, other than the US, offer birthright citizenship”. February 6, Aljazeera, Doha, Qatar.

Jeyaretnam, Miranda (2025) “How Does Birthright Citizenship in the U.S. Compare to the Rest of the World?”. January 23, Time, Washington, D.C.

Moslimani, Mohamad and Jeffery S, Passel (2024) “What the data says about immigrants in the U.S.” September 24, Pew Research Center, Washington, D.C.

Neufeld, Dorothy (2024) “Charted: The Foreign-Born Share of the U.S. Population: (1850-2024)”. October 30, Visual Capitalist, Vancouver, Canada.

Putterman, Samantha (2025) “Donald Trump’s False claim that the US is the ‘only’ country with birthright citizenship”. January 21, PolitiFact, The Poynter Institute, Washington, D.C.

Richwine, Jasion and Steven Camarota (2025) “Births to Illegal Immigrants and Long-Term Temporary Visitors”. February 14, Center for Immigration Studies, Washington, D.C.

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It is much easier and cheaper to send money across national borders today because of new financial service providers such as Wise, Remitly, or WorldRemit, which have substantially reduced international financial transaction costs. These new financial service providers, as well as an earlier wave of improved access to banking, have massively promoted cross-country money transfers – even those of only small amount. As a result, total remittances sent to low- and middle-income countries have increased approximately twelvefold in the last 30 years and amounted to $626 billion in 2022. In fact, remittances have already outpaced other capital flows into developing countries, including foreign direct investment and official development assistance. 

In a recent publication (Tohoff et al. 2024), we examine the previously overlooked link between remittances and demographic support. Why do money transactions matter to demography? Because the interaction between the demographic composition of a country and its economy matters. As we know, during the period when a country transitions from high fertility and mortality rates to low ones, there are many working adults and relatively few dependent children and seniors. This advantageous ratio can pave the way for rapid growth, during this period and beyond. It can kickstart economic growth and poverty reduction. In other words, a country can fully cash in on its demographic dividend. 

However, if there are not enough jobs for the growing workforce, demographic transitions can go terribly wrong. High unemployment, coupled with large youth bulges, increases the risk of conflict, and can have a destabilizing effect on society. While emigration helps reduce population pressures, the demographic dividend has (historically) been lost with the exodus of workers. As we show, the burgeoning role of remittances is changing that paradigm.

A remittances-adjusted support ratio: RASR

To account for the support offered through remittances, we developed a new demographic indicator: the remittances-adjusted support ratio (RASR). We incorporate remittances into the well-established support ratio (SR) by expressing them as worker equivalents. The support ratio is generally defined as the ratio of effective workers to effective consumers in a population. To express remittances (money) as effective workers (people), we divide net remittances by a country’s average per capita labour income. This yields what we call effective shadow workers. For example, if a country receives 1 million USD in remittances and the mean annual per capita labour income of this country is 10,000 USD, then this equates to 100 shadow workers. The money sent by migrants is equal to 100 average annual incomes back home or, in other words, the remittances are equivalent to the support of 100 average workers. To calculate the RASR, we simply add these shadow workers to the numerator of the established support ratio, thereby incorporating their supportive role into the indicator. 

Adjusting for remittances may make a large difference

Our findings reveal significant differences between traditional support ratios and the remittances-adjusted support ratio, particularly in middle-income countries (Figure 1). Even as early as the 1990s, the remittances adjustment makes a clearly visible difference, and the gap between the two support ratios has steadily increased since then. Today, the remittance adjustment is particularly large in the Caribbean, Central America, Southern Asia, Eastern Europe, and Central Asia. In the Philippines, for instance, the RASR is more than 10 percent larger than the classical support ratio; in El Salvador it is more than 30 percent larger, underscoring the pivotal role of remittances in bolstering demographic support. 

In high income countries, the RASR is not notably different from the classical support ratio, as (negative) net remittances divided by high average incomes yield a negligible number of (negative) shadow workers. In Germany, the US, or the UK, for instance, we see basically no effect of remittances on demographic support. When migrants work in these high-income countries, they might even play a dual supporting role. They support their host country by working and paying taxes and they support people in their country of origin via remittances. 

Promoting migration while facilitating remittances may now be an attractive policy approach for countries facing a large youth bulge and too few employment opportunities. Such a solution is not equivalent to keeping and employing the youth at home, however. While remittances can be very valuable in supporting a country’s population in good times, they tend to make countries more dependent and vulnerable in times of global crises. Furthermore, the outflow of high-skilled workers is not in the long-term interest of developing countries, even if it leads to higher remittance inflows in the short to medium term.

It is difficult to assess the extent to which countries are already exploiting remittances as part of their growth strategies. The identification of causal links between the RASR and economic growth is ambiguous. It is plausible that the additional support of remittances leads to more economic growth. However, in a country where the economy and wages are growing fast, there is little reason for its citizens to emigrate. So, a simple correlation coefficient between remittances and economic growth will not be particularly informative.

Conclusion

The RASR shows that demographic support in many countries is much higher than the classical support ratio would suggest. Remittances already play a critical role in economic and demographic support today. Once we take them into account, we can see that a country’s demographic composition matters – not just across age groups but also across national borders. Anyone who is concerned with the demographic composition of low- and middle-income countries should therefore look not just at the people who live in the country itself, but also at citizens abroad. Important demographic support comes from people who have left their homeland but continue to support their loved ones through the power of cheap and accessible remittances. 

References

Tohoff L., Landis D., Mencarini L., Aassve A. (2024) Remittances-Adjusted Support Ratio, Population and Development Review (online first),  https://doi.org/10.1111/padr.12627

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New Zealand, Sweden, Switzerland, Australia, and Norway are the most attractive countries for highly skilled migrants in 2023. The United States would have been ranked second if visa policies were not considered.

Note: Values closer to 1(0) represent higher (lower) attractiveness. 
Source: OECD, Migration Policy Debates, N°29, March 2023.

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Population ageing affects labour supply and the sustainability of social security systems. This is particularly evident at the local level, where some territories, such as rural ones, are more exposed to rapid ageing and depopulation. In this context, internal or international migration can play a substantial role, offsetting population decline caused by low fertility in some cases, or accelerating it in others. 
Overall, the policy debate has focused on the role of international migration to rejuvenate the population, revitalise the economy and mitigate labour shortages. What is the situation in the territories of the EU?

Migration rarely compensates for negative cohort turnover in EU regions

In a recent article, we assess the relative contribution of migration to shaping the demographic evolution of the working-age population (15-64 years) of 1,166 European territories (NUTS3), separately by three classes of urbanisation: urban, intermediate, and rural (Ghio et al. 2022). We decompose the changes in the population of working age that occurred from 2015 to 2019 into: 

1) cohort turnover effects, meaning the difference between those who have just entered the working-age group (15-19 years) and those who are about to leave it (60-64 years), 

2) mortality, computed as the number of deaths occurring in the working-age population, and

3) net migration effects, calculated as a residual and corresponding to the estimated net migration for the population of working age.

While acknowledging the relevance of mortality in affecting the working-age population, we focus on the interplay between cohort turnover and migration effects, as these are more likely to be tackled by short-term policy interventions. Overall, between 2015 and 2019, 22.9 million young Europeans became part of the working-age population, while 26.6 million people reached (or were close to reaching) retirement age: this indicates a possible gap of around 3.8 million potential workers across the EU. Indeed, cohort turnover was negative in 86% of EU territories in that period. As shown in Figure 1, this happened throughout the EU, but particularly in Eastern and Central Eastern EU countries (Bulgaria, Hungary, Poland, and Romania), and Southern and South-Eastern EU countries (Croatia, Greece and Italy).

Although the working-age population shrank in most EU territories (63% of them), net migration was sufficient to counterbalance the deficit due to cohort turnover and generate an increase in the working-age population in 324 territories (27% of EU territories corresponding to 24% of the EU working-age population in 2019). They were mainly located in Germany, Austria, Sweden, and Belgium. 

Out-migration is stronger from rural areas 

On average, the working-age population decreased by 2.9% in rural areas and 1.1% in intermediate areas, but increased by 0.8% in urban areas. Looking at the geographical distribution, Figure 2 shows that positive changes in the working-age population were mostly limited to urban (144 territories) and intermediate (247 territories) areas, for instance in Austria, Belgium, Germany, Spain, France, the Netherlands and Sweden. During the 2015-2019 period, few rural areas saw an increase in their working-age populations (34 territories) and most were located in Sweden.

Although ageing affected almost all EU territories, cohort turnover effects mainly drove the decrease in working-age population in rural areas when compared to urban ones (-1.9% and -0.7% respectively). Conversely, net migration effects appeared to contribute more substantially to the size of the working-age population in urban and intermediate areas (+2.4%, and +1.4% respectively) than in rural areas (+0.4%). In short, positive net migration “ protected” urban and intermediate areas more than rural areas from further shrinkages of the labour supply.

Challenges and opportunities

Between 2015 and 2019, migration was the underlying force in the evolution of the working-age population at a fine territorial level. Although covering a limited period, our research highlights the challenges currently facing many areas, predominately rural ones, confronted with a declining working-age population due to the combination of both negative net migration and cohort effects. 

Revitalising depopulating territories and breaking the cycle of rapid ageing is a priority on the agenda of many local and national authorities (and of the European Commission). Loss of working-age population, weaker economic development and stagnation of employment are the expected consequences, calling for the urgent adoption of structural actions. Policy responses should be based on scientific evidence, pointing to the opportunities that these territories offer in terms of quality of life. For instance, less densely populated areas attracted many people (including families with young children) during the recent COVID-19 lock-downs. The adoption of teleworking increased considerably during the pandemic, making physical distance from the workplace less significant. This contributed to the “counter-urbanizationˮ movement (from urban to rural areas for permanent resettlement) observed in several countries in recent years. Furthermore, new employment opportunities, in particular in the personal services and health care sectors (Grubanov Boskovic et al. 2021) could attract a younger working-age population to the territories where ageing and depopulation are currently most severe. 

References

Ghio D., Goujon A., Natale F., 2022, Assessing the demographic impact of migration on the working age population across European territories. Demographic Research 46(9): 261–272. doi :10.4054/DemRes.2022.46.9

Grubanov Boskovic S., Ghio D., Goujon A., Kalantaryan S., Belmonte M., Scipioni M., Conte A.,Gómez-González E., Gómez E., Tolan S., Martínez-Plumed F., Pesole A., Fernández-Macías E., Hernández-Orallo J. 2021, Health and long-term care workforce: demographic challenges and the potential contribution of migration and digital technology, EUR 30593 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-76-30233-9, doi:10.2760/33427, JRC121698

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Health conditions tend to deteriorate across immigrant generations, so that first-generation immigrants frequently have better health than second and higher order generations: a process known as “negative health assimilation” (Rumbaut 1994, Hamilton et al. 2011, Mossakowski 2015). Little is known, however, about the health of children in exogamous families, where one parent is native and the other immigrant. 

Data, variables, and method

In a recent paper, we provide evidence on the role of mixed families in shaping the health gaps between different generations of immigrants in Finland (Loi et al. 2021).

The study population includes children aged 0–14 at the end of 2000, covering the 1986–2000 birth cohorts. The data derive from the Finnish population register, the Finnish hospital discharge register, and the Finnish medication purchases register. The outcomes of interest are health care records on somatic conditions, mental disorders and injuries.

• Somatic conditions include all types of conditions, such as, for instance, cancer, severe infections, asthma, epilepsy, and type 1 diabetes.

• Mental disorders include any psychopathology, such as mental and behavioral disorders due to psychoactive substance use, mood/affective disorders, neurotic syndromes, behavioral and emotional disorders.

• Injuries include all types of injuries, such as burns, poisoning, and toxic effects of substances.

The study group includes the following categories of children:

• native (the reference category): born in Finland or abroad to native parents;

• first-generation immigrant: born abroad to parents who were also born abroad;

• second-generation: born in Finland to parents who were born abroad and later migrated to Finland; and

• 2.5-generation: born to one native and one immigrant parent.

We further divide children of the 2.5 generation into those who have an immigrant mother and those who have an immigrant father. 

We pool all the person-years and apply logistic regressions with standard errors clustered by individual. We estimate three models for each of the outcomes. These are:

• model 1, where we study the relationship between immigrant generation and health,

• model 2, where we include family socioeconomic resources, and

• model 3, where we include stressors experienced in early childhood.

The generational health gradient

Adolescents with one immigrant and one native parent have a higher level of health care needs than adolescents whose parents are either both immigrants or both native. This holds especially for mental health problems.

Figure 1 shows the health gaps across immigrant generations on any cause of health care need, compared to natives. In Model 1 we observe a general pattern of increasing risk of receiving care over the immigrant generations. Compared with natives, first-generation immigrants have a lower risk. This result reflects a selection mechanism: adolescents who were born abroad and immigrated with their parents benefit from a positive health selection, which is typical of first-generation immigrants (Abraído-Lanza et al. 1999; Kennedy et al. 2006). For the second generation, the risk of receiving care is similar to that of natives, while 2.5-generation children face a higher risk, especially if the foreign-born parent is the father.

In Model 2, we refine the analysis and test whether family demographic and socioeconomic characteristics contribute to explaining the health differences across immigrant generations. We include mother’s age at childbirth and education, whether information on the father is missing, and household income. Although associated with the outcome, these characteristics do not help to significantly reduce the health gaps across generations. In Model 3, we test whether stressors that occurred earlier in childhood can help explain the pattern. These stressors include whether the adolescent’s parents divorced before the his or her 10th birthday, whether the child lives in a two-parent family, and whether the mother has mental health problems. Living in a two-parent family is associated with a lower risk of receiving care, whereas parental divorce before the child’s 10th birthday is associated with poorer health. Having a mother with a mental health condition is associated with a higher risk of poor health in adolescence. Once again, all these mechanisms help explain part of the difference across immigrant generations, but not all of it. 

Differences by cause of health care needs

Figure 2 shows the association between immigrant generation and health care needs by cause: mental disorders, somatic conditions, and injuries. Health differences compared with natives across generations of adolescents are particularly strong in the case of mental health: children of the first and second generation have a lower risk of receiving treatment for mental disorders, suggesting a persistence of the health advantage.  

Children with one native and one immigrant parent face a higher risk of mental disorders, and this relationship is stronger when the immigrant parent is the father.

Conclusions

Adolescents with one immigrant and one native parent constitute a specific health risk group. As other “explanatory” variables fail to reduce the gap with respect to the reference group, this may be a consequence either of other unobserved familial characteristics (e.g. tensions between partners) or of the broader social context in the receiving country. Adolescents with a native-born and an immigrant parent may face obstacles to integration that cause them to develop mental disorders more easily than others. These adolescents are becoming more and more numerous in immigration societies, and their health is likely to influence their later outcomes (in school, in the labor market and in social life); they probably need higher levels of care and support than they have received until now. 

Funding

This research was financially supported by the Max Planck Society within the framework of the research initiative “The Challenges of Migration, Integration and Exclusion” (WiMi).

References 

Abraído-Lanza, A. F., Dohrenwend, B. P., Ng-Mak, S. S., & Turner, J. B. (1999). The Latino mortality paradox: A test of the “salmon bias” and healthy migrant hypotheses. American Journal of Public Health, 89, 1543–1548.

Hamilton, E. R., Cardoso, J. B., Hummer, R. A., & Padilla, Y. C. (2011). Assimilation and emerging health disparities among new generations of U.S. children. Demographic Research, 25, 783–818. 

Kennedy, S., McDonald, J. T., & Biddle, N. (2006). The healthy immigrant effect and immigrant selection: Evidence from four countries (SEDAP Research Paper No. 164). Hamilton, Ontario, Canada: Social and Economic Dimensions of an Aging Population Research Program, McMaster University.

Loi S., Pitkänen J., Moustgaard H., Myrskylä M., Martikainen P.; Health of Immigrant Children: The Role of Immigrant Generation, Exogamous Family Setting, and Family Material and Social Resources. Demography 2021; 9411326.

Mossakowski, K. N. (2015). Disadvantaged family background and depression among young adults in the United States: The roles of chronic stress and self-esteem. Stress and Health, 31, 52–62.

Rumbaut, R. G. (1994). The crucible within: Ethnic identity, self-esteem, and segmented among children of immigrants. International Migration Review, 28, 748–794.

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The relationship between fertility and migration is complex, because migrants are both selected and highly heterogeneous in their migration paths and living conditions at destination. To shed light on migrant fertility, scholars should compare their behaviour with that of two non-migrant groups: those of the destination countries and those in the origin countries who did not migrate. This double comparison would help to understand whether the reproductive behaviour of migrants reflects the values, norms and traditions that they absorbed during their childhood or, conversely, is affected by their life and migration experiences. Unfortunately, this comparative approach is rarely applicable: while data in destination countries are frequently available (Beauchemin, 2014), those in origin countries typically are not, and this has led to a sort of “methodological nationalism” (Wimmer and Glick-Schiller, 2003), i.e. a tendency to view the nation-state as the unit of analysis.

As an exception, in a recent study (Impicciatore, Gabrielli and Paterno, 2020) we provided an original and comprehensive picture of migrants’ fertility in Italy, merging five different datasets. Data taken from the Italian “Social Condition and Integration of Foreigners” survey (SCIF) carried out in 2011-2012, were combined with data on non-migrants living both in Italy (Multipurpose survey on “Families and Social Subjects” – FSS 2009), and in the three most important countries of origin: Albania, Morocco and Ukraine (Demographic and Health Surveys conducted, respectively, in 2008-09, 2003-04, and 2007).

A fragmented scenario of migrants in Italy

The history of immigration to Italy is relatively recent and stratified into different periods (Buonomo et al., 2020). Foreign immigration in Italy started in the late 1970s, the main origin areas being Northern Africa (Morocco, Tunisia, and Egypt), the Middle East, and Southeast Asia (Philippines, China, and Sri Lanka). East-West migration increased during the 1990s, after the fall of the Berlin wall and the collapse of the Soviet Union, with the arrival of Albanians, and then of ex-Yugoslavian citizens during the Balkans conflict. Migration of workers from Central Europe (from countries such as Poland and Romania) increased likewise. Large numbers of refugees and asylum seekers have also arrived in recent years (Strozza and Gabrielli, 2020). Overall, there are currently around 6 million foreign residents in Italy, with widely different geographical origins, migration histories, and degrees of integration. Among the non-EU female population, Albanians, Moroccans and Ukrainians currently constitute the largest national groups (“third countries”) representing, respectively, 12.1%, 11.1% and 10.4% of the total number of resident non-EU women (Register data as of December 31, 2018).

Fertility at home and abroad

The increased number of births to immigrant parents (18% of births with at least one foreign parent in 2009, 22% in 2018) is the most immediate sign of the impact of foreigners on Italian fertility. Among migrants, however, there is considerable heterogeneity in the transition to parenthood (Mussino and Strozza, 2012; Ortensi 2015). For instance, most Ukrainian women (77%) had a child before migrating, versus only 42% of Moroccans and 45% of Albanians (Figure 1).

Median ages at first childbirth (irrespective of the child’s country of birth) (Table 1) show that the difference between migrants and stayers is negligible for women from Albania, but larger for those from Morocco and Ukraine (delay of +1.9 and +3.4 years, respectively, with respect to stayers). Figure 2 displays the Kaplan-Meier survival function, i.e. (a) the proportion of childless women, and (b) women with only one child, by age and migration background. Migrants from Ukraine are similar to stayers in that country at early ages, but they drastically reduce their propensity for childbearing after age 20. There are no significant differences in survival functions between migrants and stayers from Albania, whereas migrants from Morocco tend to postpone the first childbirth with respect to stayers. The difference disappears after age 30, however. Finally, first childbirth clearly occurs much later (compared to the other groups) among non-migrant women in Italy.

The delaying effect of migration is even more evident for the transition to second childbirth (Figure 2b): the Kaplan-Meier functions of migrants are higher than those of stayers in the three countries of origin. In particular, the pattern of migrants from Albania overlaps with that of non-migrants in Italy, whereas both migrants and stayers from Ukraine have the highest curves, indicating a delayed transition and a lower intensity (even later and lower than the Italians). Conversely, for Morocco, the two survival curves (of migrants and stayers) are relatively close to each other, and tend to converge as time since first birth increases.

Different fertility models for different migration models

Overall, among Moroccan women, childbearing is similar between movers (to Italy) and stayers (in Morocco), and significantly higher than among Italian women. This suggests the persistence of behaviours acquired in the context of origin. For first births, the fertility of Albanian women is similar for movers and stayers, but not for the second, for which Albanian women who immigrated to Italy “behave like Italians”. Ukrainians show “transition risks” (i.e. fertility behaviours) that are quite different from those of both Italian natives and Ukrainian stayers. These results are also fully confirmed by multivariate analyses (not shown here) that include, among other covariates, age at migration, thus distinguishing between children born in Italy or abroad, and taking into account the educational selectivity of migrants (see Impicciatore et al 2020).

Our results indicate that beyond individual characteristics, both migration strategies and country of origin affect fertility. Migrants from the three origin countries considered here reflect at least two different migration models in Italy. In the first classic model (observed mostly among migrants from southern and eastern Mediterranean countries), men arrive for work reasons at relatively young ages and are the “forerunners” in the process of settlement in the destination country. This is the case for Moroccans, characterized by a large proportion of single men, and also of Albanians, who tend to opt for a familial pattern, however, with a large percentage of migrant couples. The “female breadwinner” migration model observed mostly among migrants from Eastern Europe and Latin America is completely different. Here, the main actors are women, who typically arrive in Italy at an older age, with a previous family history, and are actively engaged in the labour market.

Bibliography

Beauchemin, C. (2014). A manifesto for quantitative multi-sited approaches to international migration. International Migration Review, 48(4), 921–938.

Buonomo A., Gabrielli G., Strozza S. (2020), Former Soviet Union Migration to Italy: Characteristics and Determinants of Women Condition in the Italian Labour Market, in Denisenko M., Strozza S., Light M. (eds) Migration from the Newly Independent States. 25 Years After the collapse of the USSR (pp. 295-421). Societies and Political Orders in Transition. Springer, Cham.

Impicciatore, R., Gabrielli, G. & Paterno, A. (2020). Migrants’ Fertility in Italy: A Comparison Between Origin and Destination. European Journal of Population.

Mussino, E., & Strozza, S. (2012). Does citizenship still matter? Second birth risks of resident foreigners in Italy. European Journal of Population, 28(3), 269–302.

Ortensi, L. E. (2015). Engendering the fertility-migration nexus: The role of women’s migratory patterns in the analysis of fertility after migration. Demographic Research, 32(53), 1435–1468.

Strozza S., Gabrielli G. (2020), Demographic Profile of Syrians in Italy, in Carlson E.D., Williams E.D. (eds) Comparative Demography of the Syrian Diaspora: European and Middle Eastern Destinations, European Studies of Population, Springer, Cham, 20: 237-259.

Wimmer, A., & Glick-Schiller, N. (2003). Methodological nationalism, the social sciences, and the study of migration: An essay in historical epistemology. International Migration Review, 37(3), 576–610.

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In many Western countries, the total fertility rate (TFR) of immigrant women has declined over the last decades (Figure 1). In Norway, for instance, immigrant TFR fell from 2.6 children per women in 2000 to less than 2.0 in 2017. This may be due to several factors, such as immigrants’ adaptation to the fertility norms at destination, changing composition of immigrant women by area of origin, and other factors.

In a recent study, I try to disentangle the different possible causes of this decline (Tønnessen, 2019). Like many other Northern European countries, Norway has relatively high fertility (ranging between 1.98 and 1.62 in the study period) and an increasing share of immigrants (from 5.3 per cent in 2000 to 13.8% in 2017) from all over the world and, in the last decade, from Eastern EU countries like Poland and Lithuania in particular (Statistics Norway 2020a,b).

Newly arrived family migrants explain a lot

The results show that in line with findings from many other countries (see for instance Sobotka 2008), immigrant women from regions with high fertility (such as Africa and parts of Asia) often have higher fertility in Norway than women from low fertility countries. Also, immigrant women’s fertility often declines with time since arrival in the destination country, probably because of integration, so that, everything else equal, women who have been living in Norway for a long time have lower fertility than those who arrived only recently. For instance, in 2000, newly arrived immigrants (0-2 years since migration), from Africa and Asia had a TFR above 4 children per women, while women from the same regions who had entered the country more than ten years earlier had a TFR of around 2. These trends are not particularly surprising, of course, nor is the considerably lower fertility – about 2 children per woman – of women from the European Union or the US.

However, the decline in immigrant TFR in Norway from 2000 is due neither to an increased share of immigrant women from low fertility countries, nor to an increased share of women with long duration of stay. It is linked, instead, to the fact that the fertility of recent immigrants to Norway is considerably lower than it was 20 years ago. For instance, while in 2000 the fertility of newly arrived women from Eastern and South Eastern Asia was above 4 children per women, in 2017 it was below 2. The same holds for newly arrived women from Latin America (from 3.5 in 2000 to 2.0 in 2017) and from Western and Southern Asia (4.5 to 3.5).

Decomposition methods make it possible to quantify the effect of changes in composition by duration of stay and area of origin, and the effect of changing fertility within subgroups (by duration of stay and reason for migration). The results (Table 1) show that lower fertility among newly arrived immigrants explains 93% of the overall decline, and that this is mainly driven by women from Asia.

I further analyzed this fertility decline among newly arrived women by reason for migration. Women who migrate for family reasons appear to provide a key: their share among all newly arrived immigrant women declined in this period – for instance, from above 80% in 2000 to 55% in 2017 among women from Eastern and Southern Asia – and so did their fertility (see Figure 2). Among newly arrived family migrants from Asia, TFR fell by more than two births per woman from 2000 to 2017.

Further decompositions show that the lower TFR of newly arrived family migrants accounts for a large share of the total TFR decline among all immigrants in Norway. Among newly arrived immigrants from Western and Southern Asia only, lower fertility among family migrants accounts for 10% of the overall TFR decline, and among those from Eastern and South East Asia it accounts for 8%. Hence, decreased fertility among these two groups alone accounts for 18% of the TFR decrease of all immigrant women in Norway. This is a large effect from a relatively small group; at end-2017, they represented just 3% of all immigrant women of childbearing age (5% in 2000).

A large part of this fertility decline among newly arrived family migrants from non-western parts of the world may reflect fertility declines in origin due to factors such as family planning programs or more education for women. Such factors may, in turn, affect both the share of women who migrate for family reasons and the fertility of the family migrants. And although migrant women may be a select group compared to those who remain in origin, they may have been affected by the same secular changes in fertility norms and behaviors.

Fertility has declined in many origin areas

Fertility has declined substantially in many non-western countries. Such origin area trends are sometimes overlooked in studies of immigrant fertility. Although the newly arrived immigrant women grew up in the same origin areas as those who moved to Norway one or two decades ago, they grew up in a different time, with different fertility norms and patterns.

The fact that the decreased immigrant TFR in Norway is mainly driven by lower fertility among newly arrived women, possibly reflecting declining fertility trends in their countries of origin, may remind migration researchers to look for explanations of changes in immigrant fertility beyond the destination country and the characteristics of individual migrants.

This can also be a reminder for policy makers and others not to draw too hasty conclusions about the effect of domestic policies by looking at trends in immigrant TFR. Although an immigrant woman’s fertility often declines with her duration of stay, thanks to successful integration for instance, this does not necessarily translate into a declining TFR for all immigrants, unless the share with long duration of stay increases.

The results of my research also point to the future: if fertility change in origin areas is a driver of fertility decline among many non-western newly arrived migrants, and if fertility continues to fall in important origin areas – as projected by the United Nations for high-fertility parts of the world (United Nations 2019) – we may expect further fertility declines among immigrants from these areas. Moreover, policies affecting fertility preferences in high-fertility parts of the world may, in turn, affect the fertility of Western countries’ own immigrant populations.

References

Sobotka, T. (2008). The rising importance of migrants for childbearing in Europe. Overview Chapter 7. Childbearing Trends and Policies in Europe. Demographic Research, Special Collection, 7, 225-248.

Statistics Norway (2020a). Births. Statistics from retrieved February 2020.

Statistics Norway (2020b). Immigrants and Norwegian-born to immigrant parents. Statistics from retrieved February 2020.

Tønnessen, M. (2019). Declined Total Fertility Rate Among Immigrants and the Role of Newly Arrived Women in Norway. European Journal of Population.

United Nations (2019). World population prospects: The 2019 revision. New York: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat.

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When we study the social outcomes of international migrants – such as fertility, health or education – we typically compare them with three reference groups: (i) non-migrants in the destination country, (ii) non-migrants in the origin country (iii) and immigrants from the same origin country living in different destinations. Although there is more than one potential comparison group, migration scholars almost always compare immigrants with non-migrants in the countries they move to. This focus on destination comparisons is understandable; they are easier because they only require a single data source. Comparisons with origin, on the other hand, require at least two harmonized data sources containing similar information and of requisite quality; one source for immigrant outcomes in the destination country and another for non-migrant outcomes in the origin country.

Destination comparisons also reflect a greater interest in where immigrants are living now, how their lives change after arrival, and the links between migration, integration and inequality. Nevertheless, comparisons with non-migrants in the destination only tell us part of the story about immigrants’ lives. If we additionally make comparisons with non-migrants in origin countries, then this can help us to understand why the outcomes of immigrants differ from non-migrants in the destination country. Often, immigrants are said to be “selected” from their origin populations. This might mean that those who leave a country are, for example, more highly educated or healthier than those who stay behind. These two factors are not independent. If some people are more highly educated than others, then they are probably healthier too, and vice versa. Although destination comparisons can tell us a lot about the experiences of immigrants in their new country, they say little about selection unless we compare them with the population they are selected from.

Comparing immigrants with their origin country: mortality…

In a recent study (Wallace and Wilson 2019), we compared the mortality of immigrants in the United Kingdom (UK) with non-migrants in their origin countries. Our analysis is framed around the migrant mortality advantage – a term used to describe the frequently observed situation in which immigrants have lower overall mortality than non-migrant populations at destination. It is considered advantageous because immigrants, on average, will live longer than non-migrants. Researchers often suspect that selection plays a big role in the advantage. For example, if we find that immigrants from India – a country that ranks around 130^th in the world life expectancy rankings – have lower mortality than non-migrants in the UK – a country that ranks around 30^th in the world – then it’s likely that the immigrants have, on average, lower mortality than non-migrants in India.

In our study, we estimated relative mortality, versus origin, of immigrants from the 35 countries with the largest immigrant populations in the United Kingdom, by age and sex. We analysed data on deaths and population sizes from the Office for National Statistics (in the UK) alongside equivalent data for origin countries from the Human Mortality Database and the United Nations World Population Prospects. We also analysed equivalent data on the educational attainment – of immigrants versus their country of birth – as a more widely accepted measure of selection (Feliciano and Lanuza 2017) and a characteristic that remains quite stable with time (unlike mortality, which is directly affected by people’s experiences in the destination country (Ichou and Wallace 2018).

Figure 1 shows the age-specific mortality of immigrants relative to the population in their countries of birth. The far-left panel shows the “average” for all immigrants living in the UK plotted in black, with individual immigrant groups plotted in light grey. The red line indicates mortality in origin countries at a given age. Values below the red line indicate a mortality advantage, whereas those above the red line indicate excess mortality among immigrants. The other panels show four examples of immigrant groups from countries with different levels of the Human Development Index (HDI), ranging from low (Nigeria) to very high (the United States). These examples are fairly typical of the averages for each HDI category that we show in the full paper, and they illustrate three key findings. First of all, there is a common shape across panels, in which the advantage is largest at young adult ages and decreases with age. Second, the advantage at young adult ages is largest among immigrants from poorer countries and diminishes as we move up HDI categories. Third, we find that substantial mortality advantages exist at older ages (65+) for countries in the low and medium HDI categories, but not for groups in the high and very high categories.

… and education

Figure 2 shows an almost identical analysis, but with a focus on education. Here, the far-left panel shows that immigrants almost always have higher rates of tertiary education than average members of the population in their country of birth. There are only a few exceptions (i.e. the light grey line is below the red line), with the clearest case being Lithuania (not singled out here). Generally, the size of the differentials falls as we move up HDI categories. For example, Nigerian immigrants are much more highly educated than their Nigerian origin population, whereas immigrants from the US are only somewhat more highly educated than the US average. Variation over age is likely to reflect cohort differences in migration, as well as cohort trends in the origin countries, including factors such as educational expansion.

Conclusions: selective selection at work (but weakening over time)

So, what do these findings tell us? We think that the patterns provide evidence consistent with selection. Immigrants have lower mortality than the population in their country of origin, on average. The lower the level of development in the origin country, the larger this advantage tends to be. This suggests that immigrants from poor countries need to be more strongly selected than immigrants from rich countries in order to generate a similar mortality advantage vs. the same destination population. Next, the advantage is largest at young adult ages and diminishes with age. Since the majority of immigrants arrive at young adult ages, this finding is consistent with the idea that selection effects are strongest shortly after immigrants arrive and weaken over time. In absence of data on duration of residence, it is at young adult ages that we come closest to capturing the extent of selection effects among immigrants, as these are the ages where the selection has just taken place (and exposure to life at destination is minimised). With time and a growing influence of destination-specific risk factors that affect mortality, the role of selection diminishes. Last, immigrants are also more highly educated, on average, than their origin populations. Given that education is a more stable measure of selection (because it is unlikely to change from young adulthood onwards), this result adds further support for our conclusions on mortality.

Overall, our findings represent an important reference point in the re-conceptualization of immigrant outcomes relative to origin country populations. We are not the first to make such comparisons (Marmot, Adelstein, and Bulusu 1984; Gadd et al. 2006), but our study is the first to do so for such a diverse array of countries and in such detail (i.e. by age, sex and origin country), even considering comparisons to destination. Given that selection seems to be an important explanation of the migrant mortality advantage, we should consider how the flows of selected people between countries – often from poor to rich countries – impacts positively on national mortality metrics in rich countries, negatively on national mortality in poor countries and potentially inflates the size of health inequalities between them.

Bibliography

Feliciano, C., and Y. R. Lanuza. 2017. “An immigrant paradox? Contextual attainment and intergenerational educational mobility.” Am Sociol Rev 82 (1):211-241.

Gadd, M., S. E. Johansson, J. Sundquist, and P. Wandell. 2006. “Are there differences in all-cause and coronary heart disease mortality between immigrants in Sweden and in their country of birth? A follow-up study of total populations.” BMC Public Health 6:102. doi: 10.1186/1471-2458-6-102.

Ichou, M., and M. Wallace. 2018. “The Healthy Migrant Effect: The role of educational selectivity in the good health of migrants.” Demographic Research 40 (4):61-94. doi: 10.4054/DemRes.2019.40.4.

Marmot, M.G., A.M. Adelstein, and L. Bulusu. 1984. “Lessons from the study of immigrant mortality.” The Lancet 323 (8392):1455-1457. doi: 10.1016/S0140-6736(84)91943-3.

Wallace, M., and B. Wilson. 2019. “Migrant Mortality Advantage Versus Origin and the Selection Hypothesis.” Population and Development Review 45 (4):767-+. doi: 10.1111/padr.12298.

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