Periodic Reporting for period 2 - HumMingBird (Enhanced migration measures from a multidimensional perspective)
Periodo di rendicontazione: 2020-12-01 al 2022-05-31
The HumMingBird project aims to improve the mapping and understanding of changing immigration flows into the EU. Migration has become a matter of significant social, political and broader public concern. The need for well-informed, evidence-based migration policies has therefore shifted very high on the agenda of national and EU authorities. This research analyses patterns and drivers of migration, new geographies, and tests new methods to forecast emerging and future trends. The research objectives can be summarised as follows:
• To assess the quality and comparability of existing statistical concepts and data (stocks as well as flows) relating to migration in the EU;
• To explore and validate the use of alternative data sources – including various types of big data (such as social media or telecommunication);
• To understand the changing nature of migration flows and the drivers of migration; to analyse patterns, motivations and new geographies; to hear the voices of migrants in various ‘hubs’ around Europe;
• To nowcast short-term flows and forecast longer-term patterns of migration, while identifying uncertainties;
• To examine the interactions between migration flows and policies, and
• To estimate the potential impact of alternative policy scenarios.
• To assess the quality and comparability of existing statistical concepts and data (stocks as well as flows) relating to migration in the EU;
• To explore and validate the use of alternative data sources – including various types of big data (such as social media or telecommunication);
• To understand the changing nature of migration flows and the drivers of migration; to analyse patterns, motivations and new geographies; to hear the voices of migrants in various ‘hubs’ around Europe;
• To nowcast short-term flows and forecast longer-term patterns of migration, while identifying uncertainties;
• To examine the interactions between migration flows and policies, and
• To estimate the potential impact of alternative policy scenarios.
The first step in the research (WP2) consisted in a review of theories of migration (neo¬classical migration theory, behavioural models, new economics of labour migration; dual labour market theory, world systems theory). The review focussed on the ’triggers’ as well as the perpetuation of migration (network theory, cumulative causation of migration and migration systems). In addition, a screening of statistical sources resulted in the identification of gaps in data collection. An expert workshop was held on 3-4 December 2020. This work package resulted in a report and a policy brief with recommendations for future research and data collection.
Another strand of the research (WP3 and WP8) analyses the determinants of migration flows by country of destination, including intra-EU migration of third-country nationals. The first results indicate that there is a lot of heterogeneity in the migration patterns, and that cultural proximity appears to play a greater role in the choice of destination countries than economic drivers. Nevertheless, economic motives tend to gain in importance across time. As regards migration policies, the main lessons can be summarised as follows:
• Restrictive migration policies decrease migration flows and affect their skills composition, but also produce unintended consequences, mainly increased numbers of undocumented migrants.
• Migration policies are increasingly used as a tool for migrant selection, which affects the skill composition and volume of skilled migration. However in the long term they produce the same (side) effects as restrictive policies.
• Restrictive migration and migrant integration policies create a ‘vicious circle’ of exclusion that reinforces fear and separation, while inclusive policies create a ‘virtuous circle’ of integration that promotes openness and interaction.
• Under inclusive policies, the public feels less fear of migrants, while migrants enjoy greater opportunities to participate in society. Migrants develop positive attitudes towards their identity, their health, their satisfaction with life, their trust in society and their participation in politics, as well as receiving other benefits, such as upskilling and a path to citizenship.
The bulk of the research (WP4-5-6-7) focuses on the use of big data (mobile CDR data, social media, satellite data, air traffic data, mortality data) in mapping emerging migration flows. The main focus of these work packages is on methodological development as well as the development of ethically proofed protocols for the use of data. Although each data source has their own advantages and limitations, all of them prove to be useful in producing more up-to-date indicators of migration, and indeed help understand its drivers.
- the analysis of satellite data in monitoring climate-driven migration appears to be more complex than anticipated, especially when focussing on very short-term events like hurricanes;
- social media allow for the mapping of specific subgroups (geographical origin, skill level etc.) as well as the analysis of attitudes of natives towards migrants;
- air traffic data can be used to distinguish between seasonal and long-term migration patterns, and to analyse the impact of key events (e.g. Brexit);
- mortality data have been used to estimate stock figures of undocumented migrants;
- mobile CDR data appear to be useful in monitoring big refugee flows.
Qualitative research methods (WP9) are being applied to get a deeper understanding of the perspectives of migrants themselves. Both settled migrants and migrants 'en route' are being interviewed. This part of the research is still ongoing.
Another strand of the research (WP3 and WP8) analyses the determinants of migration flows by country of destination, including intra-EU migration of third-country nationals. The first results indicate that there is a lot of heterogeneity in the migration patterns, and that cultural proximity appears to play a greater role in the choice of destination countries than economic drivers. Nevertheless, economic motives tend to gain in importance across time. As regards migration policies, the main lessons can be summarised as follows:
• Restrictive migration policies decrease migration flows and affect their skills composition, but also produce unintended consequences, mainly increased numbers of undocumented migrants.
• Migration policies are increasingly used as a tool for migrant selection, which affects the skill composition and volume of skilled migration. However in the long term they produce the same (side) effects as restrictive policies.
• Restrictive migration and migrant integration policies create a ‘vicious circle’ of exclusion that reinforces fear and separation, while inclusive policies create a ‘virtuous circle’ of integration that promotes openness and interaction.
• Under inclusive policies, the public feels less fear of migrants, while migrants enjoy greater opportunities to participate in society. Migrants develop positive attitudes towards their identity, their health, their satisfaction with life, their trust in society and their participation in politics, as well as receiving other benefits, such as upskilling and a path to citizenship.
The bulk of the research (WP4-5-6-7) focuses on the use of big data (mobile CDR data, social media, satellite data, air traffic data, mortality data) in mapping emerging migration flows. The main focus of these work packages is on methodological development as well as the development of ethically proofed protocols for the use of data. Although each data source has their own advantages and limitations, all of them prove to be useful in producing more up-to-date indicators of migration, and indeed help understand its drivers.
- the analysis of satellite data in monitoring climate-driven migration appears to be more complex than anticipated, especially when focussing on very short-term events like hurricanes;
- social media allow for the mapping of specific subgroups (geographical origin, skill level etc.) as well as the analysis of attitudes of natives towards migrants;
- air traffic data can be used to distinguish between seasonal and long-term migration patterns, and to analyse the impact of key events (e.g. Brexit);
- mortality data have been used to estimate stock figures of undocumented migrants;
- mobile CDR data appear to be useful in monitoring big refugee flows.
Qualitative research methods (WP9) are being applied to get a deeper understanding of the perspectives of migrants themselves. Both settled migrants and migrants 'en route' are being interviewed. This part of the research is still ongoing.
HumMingBird aims to innovate in two ways. Firstly, various types of big data are being used to ‘nowcast’ (or at least, monitor very closely) emerging migration flows. A variety of big data sources are used for this purpose: satellite maps to measure the impact of climate change and environmental disasters such as floods or droughts; the use of social media; quantitative (geo-located) indicators of telephone conversations; data on deaths of undocumented residents.
Secondly, in-depth qualitative research is ongoing on the perspective of migrants themselves. In addition to interviews with settled migrants, anthropological research will be conducted in some key ‘migration hubs’, i.e. transit places where migrants ‘en route’ reside for a while and often adjust their plans depending on the information on obstacles and opportunities that they collect.
Secondly, in-depth qualitative research is ongoing on the perspective of migrants themselves. In addition to interviews with settled migrants, anthropological research will be conducted in some key ‘migration hubs’, i.e. transit places where migrants ‘en route’ reside for a while and often adjust their plans depending on the information on obstacles and opportunities that they collect.