The data presented in this data project were collected in the context of two H2020 research projects: ‘Enhanced migration measures from a multidimensional perspective’(HumMingBird) and ‘Crises as opportunities: Towards a level telling field on migration and a new narrative of successful integration’(OPPORTUNITIES). The current survey was fielded to investigate the dynamic interplay between media representations of different migrant groups and the governmental and societal (re)actions to immigration. With these data, we provide more insight into these societal reactions by investigating attitudes rooted in values and worldviews. Through an online survey, we collected quantitative data on attitudes towards: Immigrants, Refugees, Muslims, Hispanics, Venezuelans News Media Consumption Trust in News Media and Societal Institutions Frequency and Valence of Intergroup Contact Realistic and Symbolic Intergroup Threat Right-wing Authoritarianism Social Dominance Orientation Political Efficacy Personality Characteristics Perceived COVID-threat, and Socio-demographic Characteristics For the adult population aged 25 to 65 in seven European countries: Austria Belgium Germany Hungary Italy Spain Sweden And for ages ranged from 18 to 65 for: United States of America Colombia The survey in the United States and Colombia was identical to the one in the European countries, although a few extra questions regarding COVID-19 and some region-specific migrant groups (e.g. Venezuelans) were added. We collected the data in cooperation with Bilendi, a Belgian polling agency, and selected the methodology for its cost-effectiveness in cross-country research. Respondents received an e-mail asking them to participate in a survey without specifying the subject matter, which was essential to avoid priming. Three weeks of fieldwork in May and June of 2021 resulted in a dataset of 13,645 respondents (a little over 1500 per country). Sample weights are included in the dataset and can be applied to ensure that the sample is representative for gender and age in each country. The cooperation rate ranged between 12% and 31%, in line with similar online data collections.

Global matrices of bilateral migrant stocks spanning the period 1960-2000, disaggregated by gender and based primarily on the foreign-born concept are presented. Over one thousand census and population register records are combined to construct decennial matrices corresponding to the last five completed census rounds.For the first time, a comprehensive picture of bilateral global migration over the last half of the twentieth century emerges. The data reveal that the global migrant stock increased from 92 to 165 million between 1960 and 2000. South-North migration is the fastest growing component of international migration in both absolute and relative terms. The United States remains the most important migrant destination in the world, home to one fifth of the world™s migrants and the top destination for migrants from no less than sixty sending countries. Migration to Western Europe remains largely from elsewhere in Europe. The oil-rich Persian Gulf countries emerge as important destinations for migrants from the Middle East, North Africa and South and South-East Asia. Finally, although the global migrant stock is still predominantly male, the proportion of women increased noticeably between 1960 and 2000.

The DEMIG-QuantMig Migration Policy Database tracks more than 7'600 migration policy changes enacted by 31 European (EU and non-EU) countries for the period 1990 to 2020. This database extendeds and updates the DEMIG POLICY database (https://www.migrationinstitute.org/data/demig-data/demig-policy) and follows the same methodology. The policy measures are coded according to the policy area and migrant group targeted, as well as the change in restrictiveness they introduce in the existing legal system. The database allows for both quantitative and qualitative research on the long-term evolution and effectiveness of migration policies.

Migration data in EU in 2023 based on Eurostat datasets.

Including: People living in the EU in 2023, Foreign-born residents per country, Reasons to stay in Europe, Employment of immigrants, Refugees in Europe, Migration to and from the EU, Seeking asylum in Europe, Irregular border crossings

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The data presented in this data project were collected in the context of two H2020 research projects: ‘Enhanced migration measures from a multidimensional perspective’(HumMingBird) and ‘Crises as opportunities: Towards a level telling field on migration and a new narrative of successful integration’(OPPORTUNITIES). The current survey was fielded to investigate the dynamic interplay between media representations of different migrant groups and the governmental and societal (re)actions to immigration. With these data, we provide more insight into these societal reactions by investigating attitudes rooted in values and worldviews. Through an online survey, we collected quantitative data on attitudes towards: Immigrants, Refugees, Muslims, Hispanics, Venezuelans News Media Consumption Trust in News Media and Societal Institutions Frequency and Valence of Intergroup Contact Realistic and Symbolic Intergroup Threat Right-wing Authoritarianism Social Dominance Orientation Political Efficacy Personality Characteristics Perceived COVID-threat, and Socio-demographic Characteristics For the adult population aged 25 to 65 in seven European countries: Austria Belgium Germany Hungary Italy Spain Sweden And for ages ranged from 18 to 65 for: United States of America Colombia The survey in the United States and Colombia was identical to the one in the European countries, although a few extra questions regarding COVID-19 and some region-specific migrant groups (e.g. Venezuelans) were added. We collected the data in cooperation with Bilendi, a Belgian polling agency, and selected the methodology for its cost-effectiveness in cross-country research. Respondents received an e-mail asking them to participate in a survey without specifying the subject matter, which was essential to avoid priming. Three weeks of fieldwork in May and June of 2021 resulted in a dataset of 13,645 respondents (a little over 1500 per country). Sample weights are included in the dataset and can be applied to ensure that the sample is representative for gender and age in each country. The cooperation rate ranged between 12% and 31%, in line with similar online data collections.

The empirical dataset is derived from a survey carried out on 25 estates in 14 cities in nine different European countries: France (Lyon), Germany (Berlin), Hungary (Budapest and Nyiregyha´za), Italy (Milan), the Netherlands (Amsterdam and Utrecht), Poland (Warsaw), Slovenia (Ljubljana and Koper), Spain (Barcelona and Madrid), and Sweden (Jo¨nko¨ping and Stockholm). The survey was part of the EU RESTATE project (Musterd & Van Kempen, 2005). A similar survey was constructed for all 25 estates.

The survey was carried out between February and June 2004. In each case, a random sample was drawn, usually from the whole estate. For some estates, address lists were used as the basis for the sample; in other cases, the researchers first had to take a complete inventory of addresses themselves (for some deviations from this general trend and for an overview of response rates, see Musterd & Van Kempen, 2005). In most cities, survey teams were hired to carry out the survey. They worked under the supervision of the RESTATE partners. Briefings were organised to instruct the survey teams. In some cases (for example, in Amsterdam and Utrecht), interviewers were recruited from specific ethnic groups in order to increase the response rate among, for example, the Turkish and Moroccan residents on the estates. In other cases, family members translated questions during a face-to-face interview. The interviewers with an immigrant background were hired in those estates where this made sense. In some estates it was not necessary to do this because the number of immigrants was (close to) zero (as in most cases in CE Europe).

The questionnaire could be completed by the respondents themselves, but also by the interviewers in a face-to-face interview.

Data and Representativeness

The data file contains 4756 respondents. Nearly all respondents indicated their satisfaction with the dwelling and the estate. Originally, the data file also contained cases from the UK.

However, UK respondents were excluded from the analyses because of doubts about the reliability of the answers to the ethnic minority questions. This left 25 estates in nine countries. In general, older people and original populations are somewhat over-represented, while younger people and immigrant populations are relatively under-represented, despite the fact that in estates with a large minority population surveyors were also employed from minority ethnic groups. For younger people, this discrepancy probably derives from the extent of their activities outside the home, making them more difficult to reach. The under-representation of the immigrant population is presumably related to language and cultural differences. For more detailed information on the representation of population in each case, reference is made to the reports of the researchers in the different countries which can be downloaded from the programme website. All country reports indicate that despite these over- and under-representations, the survey results are valuable for the analyses of their own individual situation.

This dataset is the result of a team effort lead by Professor Ronald van Kempen, Utrecht University with funding from the EU Fifth Framework.

This paper examines the political attributes of emigrants and how their departure affects the electoral outcomes in their home countries. I argue that emigrants are different from those who remain in their political preferences as well as economic profiles, such that large-scale emigration changes the distribution of voters in sending countries. Emigration can also directly affect the policy preferences of individuals who stay in their home countries. I test these arguments in seven Central and Eastern European countries, using individual-level surveys and region-level data on emigration and elections. To address potential endogeneity issues, I use instrumental variable analysis, leveraging the surge of Polish emigration to the UK after the EU enlargement. I find that emigrants from Central and Eastern Europe tend to be younger, highly educated, and politically more progressive and that the vote shares of far-right parties are larger in regions with higher emigration rates. Also, I find that exposure to large-scale emigration affects the vote choices of individuals who remain behind.

This table contains 25 series, with data for years 1955 - 2013 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...) Last permanent residence (25 items: Total immigrants; France; Great Britain; Total Europe ...).

Full edition for scientific use. In 2015, Austria was one of the EU countries that received the most refugees in relation to its population (including Sweden, Hungary and Germany). One urgent concern for the integration of these migrants is for them to quickly achieve economic independence by integrating them into the labour market. Successful labour market integration depends not only on formal requirements, most notably recognized qualifications and language skills, but also on the extent of integration into other areas of society, including the integration into social networks or the identification with Austrian norms and values. This is the starting point for the present project which investigates the labour market integration of refugees and the interrelation of economic, social, and cultural integration using a standardised survey combined with a number of expert interviews and problem-centered interviews among newly arrived refugees.

The MIFARE survey was designed to focus on immigrants who migrated to the receiving country at an age of 16 years or older. The MIFARE survey has been conducted in three countries: Denmark, Germany and the Netherlands. All three countries have the opportunity to sample from population registers, including migrants. The opportunity to sample randomly from the registers enables us to test for representativeness of the survey, to approach migrant groups that are smaller in number, and guarantees comparable designs in the three countries. We propose to sample migrants from the age of 18 and older, and a native control group (to be able to compare between migrants and natives also for the questions specifically developed for the proposed survey). We choose 4 intra-EU origin countries and 6 extra-EU origin countries, including the most numerous migrant populations: Poland, Romania, Spain and the UK for the intra-EU origin countries. As extra-EU origin countries, we select China (mainland only, excluding Hong Kong), Japan, Turkey, the Philippines (not in Germany due to sampling issues), Russia, and the US. China and Turkey are the only countries not included in either the ISSP or ESS.

The short survey on current questions on migration / integration was conducted by the opinion research institute Kantar on behalf of the Press and Information Office of the Federal Government. During the survey period 18.01.2023 to 24.01.2023, the German-speaking population aged 14 and over was surveyed in telephone interviews (CATI) on their attitudes toward migration and integration. The focus is on attitudes toward refugee issues and citizenship law. Respondents were selected by a multi-stage random sample in a multi-topic survey (Emnid-bus) including landline and mobile phone numbers (dual-frame sample). Concerns about the current numbers of refugees in Germany; short-term and long-term prognosis regarding the advantages or disadvantages for Germany of accepting refugees; agreement with statements on the subject of immigration to Germany (integration of immigrants into German society has been good so far, all in all, there are already so many immigrants living in Germany that no more can be taken in, crime in Germany is rising very sharply as a result of immigration, I think it is good that Germany is becoming more culturally diverse as a result of immigration); satisfaction with the federal government´s immigration policy in various areas (dealing with the population´s concerns about immigration, how the goals and measures of immigration policy are explained to the population, efforts to date to integrate immigrants into the German labor market, efforts to date to find a European solution for immigration to Europe); opinion on rather simplified or rather more difficult regulations for immigration for the following groups: refugees from Ukraine, refugees from Syria or Afghanistan, refugees from other countries, skilled workers from non-European countries; attitude towards citizenship law (German citizenship in the future not after 8 years but already after 5 years in Germany, no giving up of citizenship of the country of origin, no naturalisation test and only simple knowledge of German if older than 67 years). Demography: sex; age; education; employment status; household size; number of persons in the household aged 14 and over; party preference; voter eligibility; net household income; survey by mobile or landline. Additonally coded were: current respondent number; weighting factor; interview date; city size (BIK regions); federal state; survey area west/ east. Die Kurzumfrage über aktuelle Fragen zur Migration / Integration wurde vom Meinungsforschungsinstitut Kantar im Auftrag des Presse- und Informationsamtes der Bundesregierung durchgeführt. Im Erhebungszeitraum 18.01.2023 bis 24.01.2023 wurde die deutschsprachige Bevölkerung ab 14 Jahren in telefonischen Interviews (CATI) zu ihrer Einstellung zu Migration und Integration befragt. Schwerpunkt ist dabei die Einstellung zu Flüchtlingsfragen und zum Staatsangehörigkeitsrecht. Die Auswahl der Befragten erfolgte durch eine mehrstufige Zufallsstichprobe im Rahmen einer Mehrthemenbefragung (Emnid-Bus) unter Einschluss von Festnetz- und Mobilfunknummern (Dual-Frame Stichprobe). Sorgen über die aktuellen Flüchtlingszahlen in Deutschland; kurzfristige und langfristige Prognose hinsichtlich der Vorteile oder Nachteile für Deutschland durch die Aufnahme von Flüchtlingen; Zustimmung zu Aussagen zum Thema Einwanderung nach Deutschland (Integration der Einwanderer in die deutsche Gesellschaft ist bisher alles in allem gut gelungen, in Deutschland leben schon so viele Einwanderer, dass keine weiteren aufgenommen werden können, durch Einwanderung steigt die Kriminalität in Deutschland sehr stark an, ich finde es gut, dass Deutschland durch Einwanderung kulturell vielfältiger wird); Zufriedenheit mit der Einwanderungspolitik der Bundesregierung in verschiedenen Bereichen (Umgang mit den Sorgen der Bevölkerung zum Thema Einwanderung, wie Ziele und Maßnahmen der Einwanderungspolitik der Bevölkerung erklärt werden, bisherige Bemühungen zur Integration von Einwanderern in den deutschen Arbeitsmarkt, bisherige Bemühungen um eine europäische Lösung für die Einwanderung nach Europa); Meinung zu eher vereinfachten oder eher erschwerten Regelungen der Zuwanderung für folgende Gruppen (Flüchtlinge aus der Ukraine, Flüchtlinge aus Syrien oder Afghanistan, Flüchtlinge aus anderen Ländern, Fachkräfte aus dem nicht-europäischen Ausland); Einstellung zum Staatsangehörigkeitsrecht (deutsche Staatsangehörigkeit künftig nicht mehr nach 8 Jahren sondern bereits nach 5 Jahre in Deutschland, kein Aufgeben der Staatsangehörigkeit des Herkunftslandes, kein Einbürgerungstest und nur einfache Deutschkenntnisse wenn älter als 67 Jahre). Demographie: Geschlecht; Alter; Bildung; Berufstätigkeit; Haushaltsgröße; Anzahl der Personen im Haushalt ab 14 Jahren; Parteipräferenz; Wahlberechtigung; Haushaltsnettoeinkommen; Erhebung per Mobilfunk oder Festnetz. Zusätzlich verkodet wurde: laufende Befragtennummer; Gewichtungsfaktor; Interviewdatum; Ortsgröße (BIK-Regionen); Bundesland; Befragungsgebiet West/Ost.

European countries are experiencing population decline and the tacit assumption in most analyses is that the decline may have detrimental welfare effects. In this paper we use a survey among the population in the Netherlands to discover whether population decline is always met with fear. A number of results stand out: population size preferences differ by geographic proximity: at a global level the majority of respondents favors a (global) population decline, but closer to home one supports a stationary population. Population decline is clearly not always met with fear: 31 percent would like the population to decline at the national level and they generally perceive decline to be accompanied by immaterial welfare gains (improvement environment) as well as material welfare losses (tax increases, economic stagnation). In addition to these driving forces it appears that the attitude towards immigrants is a very strong determinant at all geographical levels: immigrants seem to be a stronger fear factor than population decline. The data was collected from a Dutch household panel.

Using a multilevel modelling approach to analyse a novel dataset of academic publications at all business schools in 11 European countries, this paper finds that the influence of organisational- and country-level contextual factors on researchers varies considerably based on the type of institution and the development level of the country they are located in. At the organisational-level, we find that greater spatial connectivity–operationalised through proximity to nearby business schools, rail stations, and airports–is positively related to scientific research volume and public dissemination (news mentions). While this result is significant only for high-income countries (above EU-average 2018 GDP per capita), this is likely because the low-income countries (below EU-average 2018 GDP per capita) examined here lack a ‘critical mass’ of well-connected universities to generate observable agglomeration effects. At the country-level, the results indicate that in high-income countries, less prestigious schools benefit from higher rates of recent international immigration from any foreign country, providing a direct policy pathway for increasing research output for universities that aren’t already well-known enough to attract the most talented researchers. In low-income countries, recent immigration rates are even stronger predictors of research performance across all levels of institutional prestige; more open immigration policies would likely benefit research performance in these countries to an even greater extent. Finally, the paper’s results show that, in low-income countries, a composite measure of a country’s quality of life (including self-rated life satisfaction, health, working hours, and housing overcrowding) is positively related to research outcomes through its interaction with school prestige. This suggests that the lower a country’s quality of life, the more researchers are incentivised to produce higher levels of research output. While this may in part reflect the greater disparities inherent in these countries’ economic systems, it is noteworthy–and perhaps concerning–that we have observed a negative correlation between country-level quality of life and research performance in low-income countries, which is particularly felt by researchers at less prestigious institutions.

The Migrant Integration Policy Index (MIPEX) is a unique tool which measures policies to integrate migrants in countries across fifty six continents, including all EU Member States (including the UK), other European countries (Albania, Iceland, North Macedonia, Moldova, Norway, Serbia, Switzerland, Russia, Turkey and Ukraine), Asian countries (China, India, Indonesia, Israel, Japan, Jordan, Saudi Arabia, South Korea, United Arab Emirates), North American countries (Canada, Mexico and US), South American countries (Argentina, Brazil, Chile), South Africa, and Australia and New Zealand in Oceania. Policy indicators have been developed to create a rich, multi-dimensional picture of migrants’ opportunities to participate in society. In the fifth edition (MIPEX 2020), a core set of indicators were created and updated for the period 2014-2019. MIPEX now covers the period 2007-2019 and is being updated to cover the 2020-2023 period. The index is a useful tool to evaluate and compare what governments are doing to promote the integration of migrants in all the countries analysed. MIPEX scores are based on a set of indicators covering eight policy areas that has been designed to benchmark current laws and policies against the highest standards through consultations with top scholars and institutions using and conducting comparative research in their area of expertise. The policy areas of integration covered by the MIPEX are the following: Labour market mobility; Family reunification; Education; Political participation; Permanent residence; Access to nationality; Anti-discrimination; and Health.

The 2000 Families: Migration Histories of Turks in Europe project explores migration processes, the multi-generational transmission of social, cultural, religious and economic resources, values and behavior. The research is targeted Turkish migrant and non-migrant families, their members in European countries and those who did not migrate to European countries or returned to Turkey, and involves survey interviews with approximately 6000 family members across three generations.

The study consists of three parts: Family Tree (Pilot and Main), Proxy interviews (Pilot and Main) and Personal interviews (Pilot and Main).

I. Information on first generation man (IKE): male ancestor is migrant or non-migrant; still alive; place of birth; year of birth (age); ethnic family origin; left his place of birth for more than five years; migration within Turkey; country of first destination; place of first destination (NUTS); year or age of internal migration; year or age of international emigration; ever moved to Europe for more than five years and country; year or age of moving; country of current (last) residence; duration of stay in Europe; number of siblings; place in the rank; age; sex of siblings; sibling moved to Europe between 1960-1974; emigration motive(s); spouse is alive; emigration(s) of spouse; year of emigration(s) of spouse; current (last) marriage was his first marriage; end of the first marriage; arranged marriage; year of marriage; ethnic family origin of spouse; spouse is (was) a relative; religion of spouse (or partner); highest level of education; first main job (ISCO-88 and ISEI); job title of current or last job (ISCO-88 and ISEI); kind of job; occupation of the father of IKE (ISCO-88 and ISEI); religion (denomination); left the country before he died; age or year of death; country of death; legal marital status at time of death; information on IKE´s children, grandchildren and great grandchildren.

Additionally coded was: children code; grandchildren code; rank number of children, grandchildren and great grandchildren; generation.

II. 1. Information about respondent and migration history: migration status; year of first migration; age of first migration; country of current stay (NUTS); name of the city, town or village; degree of urbanization; city is usual place of living; name of the nearest city; usual place of living, degree of urbanization, nearest city, and country of usual place of living; place of birth, and degree of urbanization; nearest city to place of birth; country of place of birth; respondent left his country for at least one year and number of countries; destination countries; age of migration; main reason for moving; regularly movement between two countries; names of these two countries;

1. Achieved education and occupation: completed education or still in education; literacy; age when finished education; country in which the respondent finished his education; highest level of education; information on first occupation and current (or last) occupation (ISCO-88 und ISEI); country of first job; occupational status; number of supervised employees; ethnic or national origin of the person who directly manages (managed) the respondent in this current or last job; number of Turkish colleagues; working hours; usual take home pay; currency; covered period of payment.

2. Family: marriage and fertility: legal marital status; stable relationship; living together with a partner; number of marriages; age when first married; end of the first marriage due to death of a partner or divorce; divorced; age when first marriage ended; age or year of first divorce; age when married current or most recent spouse; number of children; sex and age of these children.

3. Family relations: year of birth of mother and father; parents are alive; living together with parents; country of current stay; frequency of contact with parents; distance to the living place of parents; frequency of provided advice and financial support for own parents in the last 12 months; frequency of received support and financial support; attitude towards intergenerational relations and gender roles; responsible person for family finances.

4. Attachment to Turkey and to the country and identity: Turkish citizenship; feeling connected to people from Turkey; portion of friends with Turkish background; citizenship of the country of residence; feeling connected with country nationals; preferred country to win the Eurovision Song Contest;...

StatBank dataset: RAS206 Title: Immigrants 16-66 years (end November) by country of origin, length of residence, socioeconomic status, sex and age Period type: years Period format (time in data): yyyy The oldest period: 2008 The most recent period: 2023

The most important key figures about population, households, population growth, births, deaths, migration, marriages, marriage dissolutions and change of nationality of the Dutch population.

CBS is in transition towards a new classification of the population by origin. Greater emphasis is now placed on where a person was born, aside from where that person’s parents were born. The term “migration background” is no longer used in this regard. The main categories western/non-western are being replaced by categories based on continents and a few countries that share a specific migration history with the Netherlands. The new classification is being implemented gradually in tables and publications on population by origin.

Data available from: 1899

Status of the figures: All data in this publication are final data.

Changes as of 15 December 2023: None, this is a new table. This table succeeds the table population; households and population dynamics; 1899-2019. See section 3. The following changes have been made: The underlying topic leaflets about ‘migration background’ have been replaced by ‘Born in the Netherlands’ and ‘Born abroad’; The origin countries Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan, Turkmenistan and Türkiye have been assigned to the continent of Asia (previously Europe).

When will the new figures be published? The figures for the population development in 2023 and the population on 1 January 2024 will be published in the second quarter of 2024.

Are immigration policies in European countries converging? Or do some countries remain more open to immigrants than others? We address these questions through an analysis of labour migration policies in five European countries from 1990 to 2016. Using an original immigration policy index (ImPol) to measure policy restrictiveness we examine whether policies have converged, to what extent immigration regimes reflect distinct ‘varieties of capitalism’, and whether national policy trajectories are shaped by domestic politics. We find little evidence of convergence; mixed evidence that immigration policy regimes reflect capitalist diversity; and strong evidence that policies respond to changes in domestic political conditions. Whilst ‘varieties of capitalism’ may set the broad parameters for immigration regimes, the direction and timing of policy changes are determined by domestic political competition.

This database is deliverable D3.1 of the Horizon Europe project 'Global Strategy for Skills, Migration and Development' (GS4S). For more information, please see the associated working paper: Locating Shortages in Migrants’ Origin Countries: A Big Data Approach, authored by Friedrich Poeschel.

For the moment, the project collects regional-level immigration opinions data for three countries, namely Belgium, France and Great Britain. The operationalisation of ‘regions’ largely corresponds to the NUTS 1 scheme designed by the European Union. More specifically, - Belgium: Brussels, Flanders and Wallonia. - France: Nord, Bassin Parisien, Île-de-France, Est, Ouest, Centre-Est, Sud-Ouest and Méditerranée. - Great Britain: North East, North West, Yorkshire and the Humber, East Midlands, West Midlands, East of England, London, South East, South West, Scotland, Wales and Northern Ireland