ESRA logo

ESRA 2023 Glance Program

All time references are in CEST

Sampling migrants in general population surveys 2

Session Organisers Professor Francesco Molteni (University of Milan, Department of Social and Political Sciences)
Professor Riccardo Ladini (University of Milan, Department of Social and Political Sciences)
Professor Ferruccio Biolcati (University of Milan, Department of Social and Political Sciences)
TimeThursday 20 July, 16:00 - 17:30
Room U6-05

Sampling migrant groups is one of the biggest challenges in survey research. Such a challenge has been tackled by relying on both probabilistic and non-probabilistic research designs focusing on specific sub-populations (often with a local focus). With very few and remarkable exceptions (i.e., the BHPS and the SOEP), what is lacking when studying migrant populations with survey methods is the comparison with the native population, which is a key issue when looking at the differences as well as the similarities between the groups. Because of this, one of the main approaches to perform such a comparison has been to refer to the subsamples of people of foreign origin from general population surveys samples. Although the strategy has various advantages, it presents several drawbacks mainly because the low numerosity of such populations, the potential selection bias leading to the under-representation of specific migrant groups, and the variety of sampling frames, often depending on the differentiated availability and composition of population lists across contexts. The latter becomes particularly relevant in comparative research. Moving from these considerations, the session welcomes papers focusing on strategies aimed at including subsamples of migrants in general population samples. Both contributions dealing with specific techniques (i.e., oversampling techniques, onomastic procedures, focused enumeration) or practical experiences will be appreciated. In addition, also contributions reflecting on the pros and cons of using immigrant sub-samples from already existent survey programs (i.e., the European Social Survey, the European Values Study or the European Union Labour Force Survey) are welcomed.

Keywords: survey, migrants


Inequalities in Personal Networks by Migration Status in the USA: the UC Berkeley Social Networks survey

Dr Raffaele Vacca (University of Milan) - Presenting Author
Dr Basak Bilecen (University of Groningen)

Personal social networks play a crucial role in migration and migrant incorporation in different domains of social life. Studies of these networks in specific immigrant communities have grown in number in recent years, yet comparisons of migrants’ personal networks with those of non-migrants are still rare. This type of comparisons could be key to understanding inequalities, disadvantages, and resources linked to migration. This paper presents a comprehensive and systematic comparison of personal networks between three migration status groups -- first-generation migrants, migrant descendants (the "second generation"), and individuals with no migration background -- in the San Francisco Bay (SFB) area of California (USA). We use longitudinal data from the UCNets study, an innovative, general-population panel survey on social networks and health. Conducted in 3 waves (2015-2018), UCNets provides uniquely extensive and detailed information on respondents' personal networks, health behaviors and outcomes, and life events. While the study's sampling and recruitment procedures did not specifically target individuals with migration background, first-generation and second-generation migrants represented approximately 20% and 10% of respondents in Wave 1, respectively, due to the high ethnic diversity levels of the SFB general population. We find that the size of personal networks varies significantly between migration groups, even when controlling for other sociodemographic characteristics. The average first-generation migrant has a significantly smaller network and more limited access to social support in all domains – including social companionship, emotional support, and everyday practical support – compared to non-migrants and the second generation. As expected, first-generation migrants also have more geographically dispersed networks. There is little evidence, however, that migrants’ networks are characterized by higher prevalence of difficult relationships and strong ties, contrary to certain descriptions in migration literature. Family and household structures are also similar across the three groups.

Children of immigrants and labor market achievement: a (provisional) assessment of the ethnic penalty in Italy

Mr Giorgio Piccitto (University of Bologna) - Presenting Author

Recently the study of the children of immigrants in Europe is gaining momentum and broadening its range and scope (Heat et al., 2008). This group has to face the ethnic penalty, namely the gap between immigrants’ children and natives in labor market achievement after having accounted for the individual characteristics. While the literature has studied this issue in country which historically were destination of migration flows, little is known on ‘new’ receiving countries like Italy (Gabrielli and Impicciatore, 2022). Italy represents a theoretically interesting case study: it is characterized by a weak socio-economic integration of migrants, which have similar (or higher) chances to be employed than natives, due to their availability to fill the lower strata of the occupational hierarchy, but they are remarkably penalized in terms of the socio-economic status of their job. Since Italy is a country which only recently has surged as important destination of migration flows, the quota of immigrants’ children active into the labor market is significantly lower that of the old migration countries, and this prevents to provide an assessment of their performance in the labor market. In this work, we aim at filling this gap by exploiting a particularly fortunate source of data represented by two Eurostat “ad hoc modules” of the 2008 and 2014 European Union Labour Force Survey (EU-LFS). Applying multivariate statistical techniques to these data, we are able to (provisionally) shed light on the labor market situation of the immigrants’ children.

Religious tradition, destination contexts and personal characteristics: using ESS data to study migrants’ perceived discrimination

Dr Francesco Molteni (University of Milan, Department of Social and Political Sciences) - Presenting Author
Miss Arianna Pellicciotti (University of Milan)

When studying processes of migrants’ discrimination, their perception – namely the feeling of being the target of some kind of discrimination, regardless of the fact that the discriminatory act is actually being perpetrated or not – is often overlooked. This is problematic because such a perception is likely to result in a higher degree of identification with the minority group and in more visible ethnic and religious “markers”. Not surprisingly, this can reverberate on many other integration outcomes.
In a context like Europe, perceived discrimination has often a religious connotation, and therefore studying the effects of both origin and destination religious traditions, together with personal characteristics, is a core issue. To do so, a promising strategy is to take advantage of the subsample of people with foreign origin from the European Social Survey data (around 60,000 individuals from 200 origin countries and living in 33 destination countries). Given the presence of information concerning the country of origin, together with a question about the perception of being member of a group discriminated against, this permits to apply a cross-classified design to contemporary study the effects of the origin religious tradition (via the “Religious Characteristics of States Dataset Project”), of the destination country (directly from ESS data on the native population), of personal characteristics, and of the interactions among them.
Notwithstanding the potential of this approach, this strategy may come with a cost, mainly because the different sampling frameworks, possible selection bias, and the need to adopt a purely comparative approach. All the pros and cons linked to this strategy, together with the main findings, will be discussed in the presentation.

Identifying forcibly displaced in national surveys

Mrs Lorenza ROssi (UNHCR ) - Presenting Author
Dr Andrej Kveder (UNHCR )
Dr Imane Chaara (Unhcr )
Mr Filip Mitrovic (Unhcr )

The proposed paper looks at live application of refugee identification questions within a general socio-economic survey context. Refugee identification is an individual trait, which can be measured directly or using a proxy response. Proxy response, most commonly as part of the household roster, is more efficient in terms of survey time and logistical complexity. The proposed experiment looks at the comparison of proxy response to direct measurement and implications for correct identification of the target population.

Refugees (and other Forcibly Displaced Persons – FDPs) are not commonly included in national statistical frameworks and accounted for in national statistics, proving it
challenging to long-term plan and measure their progress towards global compact commitments.
To achieve the statistical inclusion of FDPs into national statistical systems, the Expert Group on IDPs and Refugees Statistics (EGRISS) was mandated to draft statistical recommendations.

To contribute filling this knowledge gap, UNHCR is launching its new global Forced Displacement Survey series aimed at collecting high quality data on FDPs through nationally representative surveys in low and lower middle-income countries.
Following the international recommendations, a battery of criteria-based identification questions to identify FDPs among the host population is being designed and tested. The identification instrument includes a sequence of several survey questions to determine which criteria of the refugee determination hold for any given respondent.

In the proposed research we will be comparing proxy report from the household head to direct reports of a randomly selected individual. We will estimate key indicators related to living conditions of refugees on samples defined either by direct measurement or proxy and implications for potential bias of findings. In the conclusion we will make recommendations for approach to measurement related to criteria-based identification of the refugee status.

Surveying European migrants in the UK

Dr Mariña Fernández-Reino (Centre on Migration, Policy and Society, University of Oxford) - Presenting Author
Ms Madeleine Sumption (Centre on Migration, Policy and Society, University of Oxford)

The post-Brexit immigration system has brought significant changes for EU citizens already living in the UK, most notably the requirement to apply for status through the EU Settlement Scheme (EUSS). There is great uncertainty about the impacts of holding EUSS status on migrants, including crucial questions such as the extent to which those with pre-settled status are aware of the need to upgrade to settled status within five years and their level of comfort using their digital status. Some design features of the EUSS may disproportionally impact applicants from certain communities, though there are no official data on this aspect. To address such gaps, we are collecting new survey data relying on novel methods of non-probability quota sampling through social networking sites, which has been successfully applied in other research fields, e.g. demography, health, and political science. It has also shown potential to sample hard-to-reach populations including migrants (Pötzschke & Weiss, 2020). An important benefit of conducting a study of this kind at this precise moment in time is that Census 2021 data will be soon published and will provide a reliable benchmark to which we can directly compare the migrant sample we have drawn. The proposed survey will include questions to identify respondents' legal status and a module on migrants’ trust in the Home Office and the immigration system. We will have preliminary results on the survey data collected by the end of March and the first paper based on these data will be ready by early summer.