Immigrant integration remains a pressing issue for policymakers in Europe and beyond, and monitoring reports offer a useful resource for collecting evidence and assessing integration outcomes and policies. This commentary highlights how integration monitoring can be a beneficial policy tool and provides insight on how to address potential challenges when developing and conducting integration monitoring.
Immigrant integration has been highly politicised across Europe and the globe amid growing polarisation on the topic, with opinionated views often drowning out evidence and science-informed discussions. That said, purely evidence-based conversations should never entirely replace political debate and inclusive deliberation.
Evidence-informed debates essential for better policies
Integration monitoring, in particular, can serve as an instrument for facilitating evidence-driven policy debates. In this regard, policymakers at the regional, national, and local (where integration happens) levels should strive to (further) develop and implement monitoring tools or make use of existing instruments. On the basis of data-driven indicators (see e.g., the Zaragoza indicators for key policy areas including employment, education, social, and political inclusion), monitoring enables policy actors to evaluate integration outcomes and provides an expedient resource for adjusting policies.
Over the past decade, in fact, numerous successful monitoring tools have been developed at different levels of governance. A prominent example of integration monitoring at the international level is the OECD/EU report Settling In: Indicators of Immigrant Integration, which was published in 2023 for the fourth time since 2012. Comparative monitoring, like the OECD/EU programme, enables the identification of national or local particularities, more effective interpretation of national/local findings, and the recognition of common (regional) challenges and trends. The latest Settling In report highlights, among other important insights for policymakers, the higher educational attainment levels of recent immigrants across Europe. It also stresses that those who are highly qualified – but who have completed their education abroad – are more likely to be overqualified for their jobs. This finding indicates that European policymakers should focus more on harnessing the existing potential of skilled migrant labour through, for instance, adjusting skill-recognition policies.
A more recent monitoring tool is the Integration Index of the Stanford/Zurich Immigration Policy Lab (IPL), which similarly aims to contribute to the accumulation of knowledge about immigrant integration outcomes through comparative study across countries and time. Employing survey data, it provides an effective monitoring template for different polities, from international to local.
The Migrant Integration Policy Index (MIPEX), which was established in 2004, is another well-known monitoring tool. In contrast to the OECD or the IPL monitoring reports, rather than focusing on the integration outcomes of immigrants and their descendants, it instead compares migrant integration policies in terms of their potential for enabling or hindering the economic, social, and political participation of migrants. The product is a comparative benchmark for different policy areas that can help policymakers and civil society actors better identify more inclusive approaches to migrant integration.
Also noteworthy are efforts by local governments, such as the City of Vienna and other localities, to conduct regular integration monitoring. Monitoring integration at the local level is particularly useful, as it is here where integration takes place and where (most commonly) pro-active, hands-on integration policies in support of newcomers and efforts to strengthen inter-group contact are forged (see e.g., the Integrating Cities Partnership). Such interventions sometimes only involve small adjustments or measures, such as the facilitation of inclusive, everyday shared spaces that, nonetheless, can facilitate integration and be implemented at the local level. Monitoring, moreover, helps equip local policy actors with data that can be deployed to advocate for potentially needed policy changes more effectively at the national level. The monitoring of the City of Vienna, for instance, regularly shows that national citizenship policies have a far-reaching effect on political participation and the quality of democracy in the city, with one-third of the population currently not able to cast their vote at the ballot box.
While monitoring tools have certainly proven to be useful instruments in informing policy debates, monitoring does not come without challenges, especially regarding design and implementation.
Conceptual clarity will bolster integration monitoring
Although integration is now a common buzzword, we still lack a broadly accepted measurement system for immigrant integration, a term that indeed means different things to different stakeholders. Conceptual clarity is, consequently, central to effective integration monitoring. Definitions matter for specifying the objectives of monitoring and selecting the methods and indicators used to measure changes over time. Take for example the following two definitions: The OECD defines integration as “the ability of immigrants to achieve the same social and economic outcomes as the native born, while taking into account their characteristics.” The IPL, for its part, defines integration as “the degree to which immigrants have the knowledge and capacity to build a successful, fulfilling life in the host society.” If the OECD definition is employed, then native-born citizens would need to serve as a reference group when monitoring integration. The IPL definition, meanwhile, places no importance on the socio-economic outcomes of the native-born population as far as integration is concerned. An approach that seeks to discern whether migrants fare better or worse than ‘natives’, notably, could be more easily instrumentalised to mobilise anti-migrant sentiment or turn complex problems – involving a range of factors such as economic status, gender, and education level – into ‘ethnic/migrant’ problems, even if this complexity is accounted for in the monitoring itself.
It is important to look at bigger societal changes, as integration processes can be epiphenomenal. Put simply, integration outcomes may change because other things change. There is thus a need to reflect on how overall developments, such as the economic development in a certain area, influence the position of migrants, and to see whether and if so, how, it affects the position of migrants and other population groups.
Policy actors should also recognise that an individual’s migrant status may not always be determinative of their socio-economic outcomes – and in some case such categories may not be empirically relevant at all. We should avoid assumptions (which are often underpinned by biases) and instead first ask whether and in which contexts the migrant category is relevant and how it interacts with other variables such as socio-economic status.
Policy actors should also carefully consider their target group for monitoring, be it the foreign-born population, first- and/or second-generation migrants, or, as is often recommended by experts, native-born children with (two) foreign-born parents (as these children were likely educated in the country and speak its language). These choices will determine the aspects of immigrant integration that are emphasised in the monitoring process. Regardless of the approach deployed, a long term-perspective that incorporates people who have been in the country a long time and their native-born descendants is important in helping evaluate and identify one of the most crucial integration boosters of all: time. Integration – unless hindered through exclusive policies or societal discrimination – happens with time.
A reflection on potential different starting positions is therefore useful, too: If, for example, a majority of the second generation of a migrant group, whose parents only had primary education, reaches secondary education levels, but only few attend university studies, this intragenerational mobility may stay undetected if integration is (exclusively) measured comparing their educational outcomes with their non-migrant peers, who may have a larger share of tertiary education. The development perspective over time, which monitoring tools offer, is key for understanding integration results.
Responsible use of monitoring data is key
A lack of data availability and harmonisation, especially in terms of cross-national comparisons and sub-national monitoring efforts, remains a major obstacle to integration monitoring. Data for smaller scale polities, such as cities and towns, is particularly scarce or simply non-existent, requiring these locales to generate their own data (e.g., through survey tools such as the IPL one), which can prove costly. Smaller localities, therefore, need financial support from the EU or national funds to implement regular integration monitoring.
Another important (statistical) challenge, especially for sub-national monitoring efforts, concerns small sample sizes when using sample data, i.e., data which does not contain information on the entire population but is based on a sample that is typically ’representative’ for the national population (such as Labour Force Surveys). A potential way to mitigate this challenge is to highlight trends based on estimates for merged time periods instead of relying on annual data.
Even at the national level, some relevant information when it comes to immigrant integration, such as reason for migration, is not available in all countries. It makes a difference if immigrant populations, for instance, are predominantly refugees or migrant workers. More generally, disaggregated data is needed. By way of illustration, the use of the ‘Asian’ demographic category could encompass a range of individuals, from high-income immigrants from South Korea to refugees from Laos, underscoring the need for analyses to heed these differences.
Regional and global cooperation should prioritise data harmonisation. As the EU example shows, even with regional integration frameworks, data harmonisation does not come quick or easy, instead requiring repeated and sustained endeavours.
Prior to data analysis, policy actors should also hold discussions with respective implementing bodies concerning how integration outcomes will be measured. Even the style in which integration outcomes are expressed, such as through percentages/share of population, can significantly shape our understanding, with varying measurement methods providing different perspectives.
The presentation format of the findings, similarly, should not be left out of these discussions. While graphic visualisations, for example, are commonly used, due diligence is needed to ensure they are user friendly and sensible. Presenting migrants solely as numbers without accompanying stories can lead to dehumanisation and ‘othering’.
Despite challenges, monitoring is critical yet first step
No matter how well thought through a monitoring exercise is, it will be impossible to accommodate all the complexity and drivers of integration processes, such as the strength of economies or varying public attitudes, to name just two.
This should not dissuade us, however, from seeking out more data and evidence to steer policy decisions. On the contrary, more polities, including sub-national governance bodies, should engage in monitoring where relevant to integration. Peer learning, EU support for exchange forums for policymakers, and streamlined approaches on methods and the harmonisation of data are certainly helpful in this regard.
Monitoring is a key instrument; however, it is only the first step in producing necessary evidence. It can help identify the state of immigrant integration, but it does not (fully) explain it. Comprehensive, in-depth investigations of the barriers to integration, causes of existing inequalities, and unequal opportunities need to follow. Such analysis, if fed into policy debates, can help to transform immigrant integration from a politicised buzzword into an effective policy programme.
Leila Hadj Abdou, Ph.D., is a part-time Assistant Professor at the Migration Policy Centre (Robert Schuman Centre for Advanced Studies) at the European University Institute in Italy and also has extensive professional experience in public administration. She is specialised in the governance of migration in the European Union.
Opinions expressed in this publication are those of the author(s) alone.