Abstract

The Human Sciences Research Council (HSRC) carried out the Migration and Remittances Survey in South Africa for the World Bank in collaboration with the African Development Bank. The primary mandate of the HSRC in this project was to come up with a migration database that includes both immigrants and emigrants. The specific activities included: · A household survey with a view of producing a detailed demographic/economic database of immigrants, emigrants and non migrants · The collation and preparation of a data set based on the survey · The production of basic primary statistics for the analysis of migration and remittance behaviour in South Africa.

Like many other African countries, South Africa lacks reliable census or other data on migrants (immigrants and emigrants), and on flows of resources that accompanies movement of people. This is so because a large proportion of African immigrants are in the country undocumented. A special effort was therefore made to design a household survey that would cover sufficient numbers and proportions of immigrants, and still conform to the principles of probability sampling. The approach that was followed gives a representative picture of migration in 2 provinces, Limpopo and Gauteng, which should be reflective of migration behaviour and its impacts in South Africa.

Geographic coverage

Two provinces: Gauteng and Limpopo

Limpopo is the main corridor for migration from African countries to the north of South Africa while Gauteng is the main port of entry as it has the largest airport in Africa. Gauteng is a destination for internal and international migrants because it has three large metropolitan cities with a great economic potential and reputation for offering employment, accommodations and access to many different opportunities within a distance of 56 km. These two provinces therefore were expected to accommodate most African migrants in South Africa, co-existing with a large host population.

Analysis unit

• Household
• Individual

Universe

The target group consists of households in all communities. The survey will be conducted among metro and non-metro households. Non-metro households include those in: - small towns, - secondary cities, - peri-urban settlements and - deep rural areas. From each selected household, one adult respondent will be selected to participate in the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Migration data for South Africa are available for 2007 only at the level of local governments or municipalities from the 2007 Census; for smaller areas called "sub places" (SPs) only as recently as the 2001 census, and for the desired EAs only back so far as the Census of 1996. In sum, there was no single source that provided recent data on the five types of migrants of principal interest at the level of the Enumeration Area, which was the area for which data were needed to draw the sample since it was going to be necessary to identify migrant and non-migrant households in the sample areas in order to oversample those with migrants for interview.

In an attempt to overcome the data limitations referred to above, it was necessary to adopt a novel approach to the design of the sample for the World Bank's household migration survey in South Africa, to identify EAs with a high probability of finding immigrants and those with a low probability. This required the combined use of the three sources of data described above. The starting point was the CS 2007 survey, which provided data on migration at a local government level, classifying each local government cluster in terms of migration level, taking into account the types of migrants identified. The researchers then spatially zoomed in from these clusters to the so-called sub-places (SPs) from the 2001 Census to classifying SP clusters by migration level. Finally, the 1996 Census data were used to zoom in even further down to the EA level, using the 1996 census data on migration levels of various typed, to identify the final level of clusters for the survey, namely the spatially small EAs (each typically containing about 200 households, and hence amenable to the listing operation in the field).

A higher score or weight was attached to the 2007 Community Survey municipality-level (MN) data than to the Census 2001 sub-place (SP) data, which in turn was given a greater weight than the 1996 enumerator area (EA) data. The latter was derived exclusively from the Census 1996 EA data, but has then been reallocated to the 2001 EAs proportional to geographical size. Although these weights are purely arbitrary since it was composed from different sources, they give an indication of the relevant importance attached to the different migrant categories. These weighted migrant proportions (secondary strata), therefore constituted the second level of clusters for sampling purposes.

In addition, a system of weighting or scoring the different persons by migrant type was applied to ensure that the likelihood of finding migrants would be optimised. As part of this procedure, recent migrants (who had migrated in the preceding five years) received a higher score than lifetime migrants (who had not migrated during the preceding five years). Similarly, a higher score was attached to international immigrants (both recent and lifetime, who had come to SA from abroad) than to internal migrants (who had only moved within SA's borders). A greater weight also applied to inter-provincial (internal) than to intra-provincial migrants (who only moved within the same South African province).

How the three data sources were combined to provide overall scores for EA can be briefly described. First, in each of the two provinces, all local government units were given migration scores according to the numbers or relative proportions of the population classified in the various categories of migrants (with non-migrants given a score of 1.0. Migrants were assigned higher scores according to their priority, with international migrants given higher scores than internal migrants and recent migrants higher scores than lifetime migrants. Then within the local governments, sub-places were assigned scores assigned on the basis of inter vs. intra-provincial migrants using the 2001 census data. Each SP area in a local government was thus assigned a value which was the product of its local government score (the same for all SPs in the local government) and its own SP score. The third and final stage was to develop relative migration scores for all the EAs from the 1996 census by similarly weighting the proportions of migrants (and non-migrants, assigned always 1.0) of each type. The the final migration score for an EA is the product of its own EA score from 1996, the SP score of which it is a part (assigned to all the EAs within the SP), and the local government score from the 2007 survey.

Based on all the above principles the set of weights or scores was developed.

In sum, we multiplied the proportion of populations of each migrant type, or their incidence, by the appropriate final corresponding EA scores for persons of each type in the EA (based on multiplying the three weights together), to obtain the overall score for each EA. This takes into account the distribution of persons in the EA according to migration status in 1996, the SP score of the EA in 2001, and the local government score (in which the EA is located) from 2007. Finally, all EAs in each province were then classified into quartiles, prior to sampling from the quartiles.

From the EAs so classified, the sampling took the form of selecting EAs, i.e., primary sampling units (PSUs, which in this case are also Ultimate Sampling Units, since this is a single stage sample), according to their classification into quartiles. The proportions selected from each quartile are based on the range of EA-level scores which are assumed to reflect weighted probabilities of finding desired migrants in each EA. To enhance the likelihood of finding migrants, much higher proportions of EAs were selected into the sample from the quartiles with the higher scores compared to the lower scores (disproportionate sampling). The decision on the most appropriate categorisations was informed by the observed migration levels in the two provinces of the study area during 2007, 2001 and 1996, analysed at the lowest spatial level for which migration data was available in each case.

Because of the differences in their characteristics it was decided that the provinces of Gauteng and Limpopo should each be regarded as an explicit stratum for sampling purposes. These two provinces therefore represented the primary explicit strata. It was decided to select an equal number of EAs from these two primary strata.

The migration-level categories referred to above were treated as secondary explicit strata to ensure optimal coverage of each in the sample. The distribution of migration levels was then used to draw EAs in such a way that greater preference could be given to areas with higher proportions of migrants in general, but especially immigrants (note the relative scores assigned to each type of person above). The proportion of EAs selected into the sample from the quartiles draws upon the relative mean weighted migrant scores (referred to as proportions) found below the table, but this is a coincidence and not necessary, as any disproportionate sampling of EAs from the quartiles could be done, since it would be rectified in the weighting at the end for the analysis.

The resultant proportions of migrants then led to the following proportional allocation of sampled EAs (Quartile 1: 5 per cent (instead of 25% as in an equal distribution), Quartile 2: 15 per cent (instead

Population in The Netherlands on 1 January by sex, age, marital status, generation and migration background.

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 1996 to 2022.

Status of the figures: All figures in the table are final.

Changes per 13 January 2023: None, this table was discontinued.

When will new figures be published? No longer applicable. This table is succeeded by the table Population; sex, age, country of origin, country of birth, 1 January. See section 3.

UK residents by broad country of birth and citizenship groups, broken down by UK country, local authority, unitary authority, metropolitan and London boroughs, and counties. Estimates from the Annual Population Survey.

This Zenodo repository contains all migration flow estimates associated with the paper "Deep learning four decades of human migration." Evaluation code, training data, trained neural networks, and smaller flow datasets are available in the main GitHub repository, which also provides detailed instructions on data sourcing. Due to file size limits, the larger datasets are archived here.

Data is available in both NetCDF (.nc) and CSV (.csv) formats. The NetCDF format is more compact and pre-indexed, making it suitable for large files. In Python, datasets can be opened as xarray.Dataset objects, enabling coordinate-based data selection.

Each dataset uses the following coordinate conventions:

• Year: 1990–2023
• Birth ISO: Country of birth (UN ISO3)
• Origin ISO: Country of origin (UN ISO3)
• Destination ISO: Destination country (UN ISO3)
• Country ISO: Used for net migration data (UN ISO3)

The following data files are provided:

• T.nc: Full table of flows disaggregated by country of birth. Dimensions: Year, Birth ISO, Origin ISO, Destination ISO
• flows.nc: Total origin-destination flows (equivalent to T summed over Birth ISO). Dimensions: Year, Origin ISO, Destination ISO
• net_migration.nc: Net migration data by country. Dimensions: Year, Country ISO
• stocks.nc: Stock estimates for each country pair. Dimensions: Year, Origin ISO (corresponding to Birth ISO), Destination ISO
• test_flows.nc: Flow estimates on a randomly selected set of test edges, used for model validation

Additionally, two CSV files are provided for convenience:

• mig_unilateral.csv: Unilateral migration estimates per country, comprising:
  • imm: Total immigration flows
  • emi: Total emigration flows
  • net: Net migration
  • imm_pop: Total immigrant population (non-native-born)
  • emi_pop: Total emigrant population (living abroad)
• mig_bilateral.csv: Bilateral flow data, comprising:
  • mig_prev: Total origin-destination flows
  • mig_brth: Total birth-destination flows, where Origin ISO reflects place of birth

Each dataset includes a mean variable (mean estimate) and a std variable (standard deviation of the estimate).

An ISO3 conversion table is also provided.

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 ...).

Many western liberal democracies have witnessed increased discrimination against immigrants and opposition to multiculturalism. Prior research identifies ethno-linguistic differences between immigrant and native populations as the key source of such bias. Linguistic assimilation has therefore been proposed as an important mechanism to reduce discrimination and mitigate conflict between natives and immigrants. Using large-scale field experiments conducted in 29 cities across Germany--a country with a high influx of immigrants and refugees--we empirically test whether linguistic assimilation reduces discrimination against Muslim immigrants in every-day social interactions. We find that it does not; Muslim immigrants are no less likely to be discriminated against even if they appear to be linguistically assimilated. However, we also find that ethno-linguistic differences alone do not cause bias among natives in a country with a large immigrant population and state policies that encourage multiculturalism.

IntroductionImmigrants were disproportionately impacted by COVID-19 and experience unique vaccination barriers. In Canada (37 million people), 23% of the population is foreign-born. Immigrants constitute 60% of the country’s racialized (non-white) population and over half of immigrants reside in Ontario, the country’s most populous province. Ontario had several strategies aimed at improving vaccine equity including geographic targeting of vaccine supply and clinics, as well as numerous community-led efforts. Our objectives were to (1) compare primary series vaccine coverage after it was widely available, and first booster coverage 6 months after its availability, between immigrants and other Ontario residents and (2) identify subgroups experiencing low coverage.Materials and methodsUsing linked immigration and health administrative data, we conducted a retrospective population-based cohort study including all community-dwelling adults in Ontario, Canada as of January 1, 2021. We compared primary series (two-dose) vaccine coverage by September 2021, and first booster (three-dose) coverage by March 2022 among immigrants and other Ontarians, and across sociodemographic and immigration characteristics. We used multivariable log-binomial regression to estimate adjusted risk ratios (aRR).ResultsOf 11,844,221 adults, 22% were immigrants. By September 2021, 72.6% of immigrants received two doses (vs. 76.4%, other Ontarians) and by March 2022 46.1% received three doses (vs. 58.2%). Across characteristics, two-dose coverage was similar or slightly lower, while three-dose coverage was much lower, among immigrants compared to other Ontarians. Across neighborhood SARS-CoV-2 risk deciles, differences in two-dose coverage were smaller in higher risk deciles and larger in the lower risk deciles; with larger differences across all deciles for three-dose coverage. Compared to other Ontarians, immigrants from Central Africa had the lowest two-dose (aRR = 0.60 [95% CI 0.58–0.61]) and three-dose coverage (aRR = 0.36 [95% CI 0.34–0.37]) followed by Eastern Europeans and Caribbeans, while Southeast Asians were more likely to receive both doses. Compared to economic immigrants, resettled refugees and successful asylum-claimants had the lowest three-dose coverage (aRR = 0.68 [95% CI 0.68–0.68] and aRR = 0.78 [95% CI 0.77–0.78], respectively).ConclusionTwo dose coverage was more equitable than 3. Differences by immigrant region of birth were substantial. Community-engaged approaches should be re-invigorated to close gaps and promote the bivalent booster.

The Swedish income panel was originally set up in the beginning of the 90s to make studies of how immigrants assimilate in the Swedish labour market possible. It consists of large samples of foreign-born and Swedish-born persons. Income information from registers is added for nearly 40 years. In addition income information relating to spouses is also available as well as for a subset of mothers and fathers. This makes it possible to construct measures of household income based on a relatively narrow definition. However, starting in 1998 there is also more information making it possible to include children over 18 and their incomes in the family. By matching with some different additional registers information has been added for people who have been unemployed or involved in labour market programmes during the 90s, on causes of deaths for people who have deceased since 1978 and on recent arrived immigrants from various origins. It has turned out that the data-base is quite useful for analysing research-questions other than originally motivating construction of the panel. The panel has been used for cross country comparisons of immigrants in the labour market and to analyse income mobility for different breakdowns of the population, and analyses the development in cohort income. There have been analyses of social assistance receipt among immigrants as well as studies of intergeneration mobility of income, the labour market situation of young immigrants and the second generation of immigrants. On-going work includes evaluation of labour market training programmes and studies of early retirement among immigrants. Planned work includes studies of the economic transition from child to adulthood during the 80s and 90s as well as studies of how frequent immigrant children are subject to measures under the Social Service Act and the Care of Youth Persons Act. The potentials of the Swedish Income Panel can be understood if one compares it with better known income-panels in other countries. For example SWIP covers more years and has a larger sample than the German Socio-Economic Panel (GSOEP). On the other hand, the fact that information is obtained from registers only makes this Swedish panel less rich in variables. There are striking parallels between the Gothenburg Income Panel and the labour market panel at the Centre for Labour Market and Social Research in Aarhus for the Danish population.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Abstract

In 1985 the population and health observatory was established at Mlomp, in the region of Ziguinchor, in southern Senegal (see map). The objective was to complement the two rural population observatories then existing in the country, Bandafassi, in the south-east, and Niakhar, in the centre-west, with a third observatory in a region - the south-west of the country (Casamance) - whose history, ethnic composition and economic situation were quite different from those of the regions where the first two observatories were located. It was expected that measuring the demographic levels and trends on those three sites would provide better coverage of the demographic and epidemiological diversity of the country.

Following a population census in 1984-1985, demographic events and causes of death have been monitored yearly. During the initial census, all women were interviewed concerning the birth and survival of their children. Since 1985, yearly censuses, usually conducted in January-February, have been recording demographic data, including all births, deaths, and migrations. The completeness and accuracy of dates of birth and death are cross-checked against those of registers of the local maternity ward (_95% of all births) and dispensary (all deaths are recorded, including those occurring outside the area), respectively. The study area comprises 11 villages with approximately 8000 inhabitants, mostly Diola. Mlomp is located in the Department of Oussouye, Region of Ziguinchor (Casamance), 500 km south of Dakar.

On 1 January 2000 the Mlomp area included a population of 7,591 residents living in 11 villages. The population density was 108 people per square kilometre. The population belongs to the Diola ethnic group, and the religion is predominantly animist, with a large minority of Christians and a few Muslims. Though low, the educational level - in 2000, 55% of women aged 15-49 had been to school (for at least one year) - is definitely higher than at Bandafassi. The population also benefits from much better health infrastructure and programmes. Since 1961, the area under study has been equipped with a private health centre run by French Catholic nurses and, since 1968, a village maternity centre where most women give birth. The vast majority of the children are totally immunized and involved in a growth-monitoring programme (Pison et al.,1993; Pison et al., 2001).

Geographic coverage

The Mlomp DSS site, about 500 km from the capital, Dakar, in Senegal, lies between latitudes 12°36' and 12°32'N and longitudes 16°33' and 16°37'E, at an altitude ranging from 0 to 20 m above sea level. It is in the region of Ziguinchor, Département of Oussouye (Casamance), in southwest Senegal. It is locates 50 km west of the city of Ziguinchor and 25 kms north of the border with Guinea Bissau. It covers about half the Arrondissement of Loudia-Ouolof. The Mlomp DSS site is about 11 km × 7 km and has an area of 70 km2. Villages are households grouped in a circle with a 3-km diameter and surrounded by lands that are flooded during the rainy season and cultivated for rice. There is still no electricity.

Analysis unit

Individual

Universe

At the census, a person was considered a member of the compound if the head of the compound declared it to be so. This definition was broad and resulted in a de jure population under study. Thereafter, a criterion was used to decide whether and when a person was to be excluded or included in the population.

A person was considered to exit from the study population through either death or emigration. Part of the population of Mlomp engages in seasonal migration, with seasonal migrants sometimes remaining 1 or 2 years outside the area before returning. A person who is absent for two successive yearly rounds, without returning in between, is regarded as having emigrated and no longer resident in the study population at the date of the second round. This definition results in the inclusion of some vital events that occur outside the study area. Some births, for example, occur to women classified in the study population but physically absent at the time of delivery, and these births are registered and included in the calculation of rates, although information on them is less accurate. Special exit criteria apply to babies born outside the study area: they are considered emigrants on the same date as their mother.

A new person enters the study population either through birth to a woman of the study population or through immigration. Information on immigrants is collected when the list of compounds of a village is checked ("Are there new compounds or new families who settled since the last visit?") or when the list of members of a compound is checked ("Are there new persons in the compound since the last visit?"). Some immigrants are villagers who left the area several years before and were excluded from the study population. Information is collected to determine in which compound they were previously registered, to match the new and old information.

Information is routinely collected on movements from one compound to another within the study area. Some categories of the population, such as older widows or orphans, frequently move for short periods of time and live in between several compounds, and they may be considered members of these compounds or of none. As a consequence, their movements are not always declared.

Kind of data

Event history data

Frequency of data collection

One round of data collection took place annually, except in 1987 and 2008.

Sampling procedure

No samplaing is done

Sampling deviation

None

Mode of data collection

Proxy Respondent [proxy]

Research instrument

List of questionnaires: - Household book (used to register informations needed to define outmigrations) - Delivery questionnaire (used to register information of dispensaire ol mlomp) - New household questionnaire - New member questionnaire - Marriage and divorce questionnaire - Birth and marital histories questionnaire (for a new member) - Death questionnaire (used to register the date of death)

Cleaning operations

On data entry data consistency and plausibility were checked by 455 data validation rules at database level. If data validaton failure was due to a data collection error, the questionnaire was referred back to the field for revisit and correction. If the error was due to data inconsistencies that could not be directly traced to a data collection error, the record was referred to the data quality team under the supervision of the senior database scientist. This could request further field level investigation by a team of trackers or could correct the inconsistency directly at database level.

No imputations were done on the resulting micro data set, except for:

a. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is greater than 180 days, the ENT event was changed to an in-migration event (IMG). b. If an out-migration (OMG) event is followed by a homestead entry event (ENT) and the gap between OMG event and ENT event is less than 180 days, the OMG event was changed to an homestead exit event (EXT) and the ENT event date changed to the day following the original OMG event. c. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is greater than 180 days, the EXT event was changed to an out-migration event (OMG). d. If a homestead exit event (EXT) is followed by an in-migration event (IMG) and the gap between the EXT event and the IMG event is less than 180 days, the IMG event was changed to an homestead entry event (ENT) with a date equal to the day following the EXT event. e. If the last recorded event for an individual is homestead exit (EXT) and this event is more than 180 days prior to the end of the surveillance period, then the EXT event is changed to an out-migration event (OMG)

In the case of the village that was added (enumerated) in 2006, some individuals may have outmigrated from the original surveillance area and setlled in the the new village prior to the first enumeration. Where the records of such individuals have been linked, and indivdiual can legitmately have and outmigration event (OMG) forllowed by and enumeration event (ENU). In a few cases a homestead exit event (EXT) was followed by an enumeration event in these cases. In these instances the EXT events were changed to an out-migration event (OMG).

Response rate

On an average the response rate is about 99% over the years for each round.

Sampling error estimates

Not applicable

Data appraisal

CenterId Metric Table QMetric Illegal Legal Total Metric Rundate
SN012 MicroDataCleaned Starts 18756 2017-05-19 00:00
SN012 MicroDataCleaned Transitions 0 45136 45136 0 2017-05-19 00:00
SN012 MicroDataCleaned Ends 18756 2017-05-19 00:00
SN012 MicroDataCleaned SexValues 38 45098 45136 0 2017-05-19 00:00
SN012 MicroDataCleaned DoBValues 204 44932 45136 0 2017-05-19 00:00

This paper presents the largest globally comparable panel database of education quality. The database includes 163 countries and regions over 1965-2015. The globally comparable achievement outcomes were constructed by linking standardized, psychometrically-robust international and regional achievement tests. The paper contributes to the literature in the following ways: (1) it is the largest and most current globally comparable data set, covering more than 90 percent of the global population; (2) the data set includes 100 developing areas and the most developing countries included in such a data set to date -- the countries that have the most to gain from the potential benefits of a high-quality education; (3) the data set contains credible measures of globally comparable achievement distributions as well as mean scores; (4) the data set uses multiple methods to link assessments, including mean and percentile linking methods, thus enhancing the robustness of the data set; (5) the data set includes the standard errors for the estimates, enabling explicit quantification of the degree of reliability of each estimate; and (6) the data set can be disaggregated across gender, socioeconomic status, rural/urban, language, and immigration status, thus enabling greater precision and equity analysis. A first analysis of the data set reveals a few important trends: learning outcomes in developing countries are often clustered at the bottom of the global scale; although variation in performance is high in developing countries, the top performers still often perform worse than the bottom performers in developed countries; gender gaps are relatively small, with high variation in the direction of the gap; and distributions reveal meaningfully different trends than mean scores, with less than 50 percent of students reaching the global minimum threshold of proficiency in developing countries relative to 86 percent in developed countries. The paper also finds a positive and significant association between educational achievement and economic growth. The data set can be used to benchmark global progress on education quality, as well as to uncover potential drivers of education quality, growth, and development.

Objective: The German Emigration and Remigration Panel Study (GERPS) is the data base developed within the project “Individuelle Konsequenzen internationaler Migration im Lebensverlauf” funded by the German Research Foundation (DFG) (project number 345626236). GERPS follows an origin-based sampling approach which allows to study individual consequences of international migrations form a life-course perspective. Apart the migration process and the sociodemographic attributes of international mobiles, the objective of GERPS is to conduct longitudinal data across the four following life domains: Employment and Income, Family and Partnership, Health and Well-being, and Social Networks and Participation. Method: The study design of GERPS exploits information from German registers within a multistage stratified probability sample of emigrants and remigrants with German citizenship aged between 20 and 70 with a documented international migration between July 2017 and June 2018. Currently GERPS is comprising four waves covering a period of 24 months. The first wave started in November 2018 and ended in February 2019. The second wave started in May 2019, six months after the beginning of wave 1. The third wave started in November 2019 and ended in January 2020, six months after the beginning of wave 2. The fourth wave is scheduled for November 2020. Wave 1 includes information about 4.545 emigrants and 6.465 remigrants. Analytical potential & Questionnaire: The research design complements traditional immigrant surveys conducted in major destination countries by surveying emigrants and remigrants from the perspective of the country of origin. The origin-based sampling approach has at least three major advantages compared to traditional approaches where samples are drawn from immigrants in their destination countries: First, it enables comparative studies of emigrants in various destination countries and of remigrants returning from different destination countries. Second, as GERPS is organized as SOEP-related study, the research design enables comparisons of the internationally mobile population with non-migrants staying in the country of origin by drawing on the German Socioeconomic Panel (SOEP). Third, the research design allows comparative studies on emigrants and remigrants, providing the opportunity to analyse consequences of international migration from at least two perspectives – shortly after emigration and shortly after return. Each wave of GERPS covers questions on German migrant’s current living situation in the different areas of life, gradually enabling researchers to draw a picture of survey participants’ life course with every further wave. Additionally, each wave has its own focus: The first wave covers migration motives and the situation shortly before migration. This enables the realization of a hypothetical fifth retrospective measurement point, allowing researchers to reflect on causes and consequences of international migration right from the beginning. The second wave concentrates on income, labour market integration, and social background. The third wave covers in particular social and family relationships. The fourth wave will be supplemented by an open module. The present study comprises the data for the third wave.

Many studies suggest that stringent labor protection and higher labor costs in host countries can limit foreign direct investment. This implies that foreign firms are sensitive to the flexibility of the labor market in the U.S. The U.S. has experienced increasing immigrants, which have preserved the stable labor supply in the U.S. market. The U.S. is a good case to test the relationship between immigration and FDI because the U.S. is not only the largest host and home country of FDI but also the country that has one of the highest immigrant populations and experiences a significant reduction in labor supply and an increase in the minimum cost of labor. Utilizing a time-series analysis from 1970 to 2016, this study suggests that the expansive immigration policies directly increase FDI inflows in the U.S., and indirectly increase FDI inflows throughout lowering potential labor costs and securing a stable labor supply.

BackgroundThe prevalence of asthma and allergic diseases is rising worldwide. Evidence on potential causal pathways of asthma and allergies is growing, but findings have been contradictory, particularly on the interplay between allergic diseases and understudied social determinants of health like migration status. This review aimed at providing evidence for the association between migration status and asthma and allergies, and to explore the mechanisms between migration status and the development of asthma and allergies.Methods and FindingsSystematic review on asthma and allergies and immigration status in accordance with the guidelines set by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The pooled odds ratio (OR) of the prevalence of asthma in immigrants compared to the host population was 0.60 (95% CI 0.45–0.84), and the pooled OR for allergies was 1.01 (95% CI 0.62–1.69). The pooled OR for the prevalence of asthma in first generation versus second generation immigrants was 0.37 (95% CI 0.25–0.58). Comparisons between populations in their countries of origin and those that emigrated vary depending on their level of development; more developed countries show higher rates of asthma and allergies.ConclusionsOur findings suggest a strong influence of the environment on the development of asthma and allergic diseases throughout the life course. The prevalence of asthma is generally higher in second generation than first generation immigrants. With length of residence in the host country the prevalence of asthma and allergic diseases increases steadily. These findings are consistent across study populations, host countries, and children as well as adults. Differences have been found to be significant when tested in a linear model, as well as when comparing between early and later age of migration, and between shorter and longer time of residence.

Objective: The German Emigration and Remigration Panel Study (GERPS) is the data base developed within the project “Individuelle Konsequenzen internationaler Migration im Lebensverlauf” funded by the German Research Foundation (DFG) (project number 345626236). GERPS follows an origin-based sampling approach which allows to study individual consequences of international migrations form a life-course perspective. Apart the migration process and the sociodemographic attributes of international mobiles, the objective of GERPS is to conduct longitudinal data across the four following life domains: Employment and Income, Family and Partnership, Health and Well-being, and Social Networks and Participation. Method: The study design of GERPS exploits information from German registers within a multistage stratified probability sample of emigrants and remigrants with German citizenship aged between 20 and 70 with a documented international migration between July 2017 and June 2018. Currently GERPS is comprising four waves covering a period of 24 months. The first wave started in November 2018 and ended in February 2019. The second wave started in May 2019, six months after the beginning of wave 1. The third wave started in November 2019 and ended in January 2020, six months after the beginning of wave 2. The fourth wave is scheduled for November 2020. Wave 1 includes information about 4.545 emigrants and 6.465 remigrants. Analytical potential & Questionnaire: The research design complements traditional immigrant surveys conducted in major destination countries by surveying emigrants and remigrants from the perspective of the country of origin. The origin-based sampling approach has at least three major advantages compared to traditional approaches where samples are drawn from immigrants in their destination countries: First, it enables comparative studies of emigrants in various destination countries and of remigrants returning from different destination countries. Second, as GERPS is organized as SOEP-related study, the research design enables comparisons of the internationally mobile population with non-migrants staying in the country of origin by drawing on the German Socioeconomic Panel (SOEP). Third, the research design allows comparative studies on emigrants and remigrants, providing the opportunity to analyse consequences of international migration from at least two perspectives – shortly after emigration and shortly after return. Each wave of GERPS covers questions on German migrant’s current living situation in the different areas of life, gradually enabling researchers to draw a picture of survey participants’ life course with every further wave. Additionally, each wave has its own focus: The first wave covers migration motives and the situation shortly before migration. This enables the realization of a hypothetical fifth retrospective measurement point, allowing researchers to reflect on causes and consequences of international migration right from the beginning. The second wave concentrates on income, labour market integration, and social background. The third wave covers in particular social and family relationships. The fourth wave will be supplemented by an open module. The present study comprises the data for the second wave.

Germany is a country known for immigration. In 2015, 21% of the general population in Germany consisted of individuals with a migration background. This article focuses on cancer-specific incidence and mortality among one of the biggest migrant groups in Germany: the resettlers. Resettlers are ethnic Germans who mainly immigrated from the Russian federation and other countries of the former Soviet Union after its collapse in 1989. We investigated differences between resettlers and the general German population, regarding (i) incidence and mortality of malignant neoplasms, (ii) time trends of the corresponding incidence and mortality, and (iii) cancer stage at diagnosis. We provide data from two resettler cohorts covering an observation time of 20 years: one cohort on cancer incidence (N = 32,972), and another cohort on mortality (N = 59,390). Cancer-specific standardized incidence ratios (SIR) and standardized mortality ratios (SMR) for all malignant neoplasms combined and the most common cancer-sites were calculated between resettlers and the general German population. Time trend analyses using Poisson regression were performed to investigate the developments of SIRs and SMRs. To investigate differences in stage at diagnosis, logistic regression was performed, calculating Odds Ratios for condensed cancer stages. We observed higher incidence and mortality of stomach cancer [SIR (men) 1.62, 95%CI 1.17–2.19; SMR (men) 1.62, 95%CI 1.31–2.01; SIR (women) 1.32, 95%CI 0.86–1.94; SMR (women) 1.52, 95%CI 1.19–1.93] and higher mortality of lung cancer [SMR (men) 1.34, 95%CI 1.20–1.50] among resettlers compared to the general German population, but lower incidence and mortality of colorectal (both sexes), lung (women), prostate and female breast cancer. However, time trend analyses showed converging incidence risks of cause-specific incidence over time, whereas differences of mortality did not show changes over time. Results from logistic regression suggest that resettler men were more often diagnosed with advanced cancer stages compared to the Münster population. Our findings suggest that risk factor patterns of the most common cancer-sites among resettlers are similar to those observed within the Russian population. Such increases in prostate, colorectal and breast cancer incidence may be the consequence of improved detection measures, and/or the adaptation of resettlers to the German lifestyle.

This strand of research was carried out between January 2010 and October 2010 and focused on 61 interviews with the providers and users of East-Central European migrant labour. The fieldwork concentrated on the hospitality and food production and processing sectors and on case study areas in urban and rural England and Scotland. The aim of this part of the research was to gain an understating of employers’ and labour providers’ experiences of recruiting and employing East-Central European labour migrants. These sectors were selected as the focus of analysis because the Worker Registration Scheme indicates that A8 migrants predominantly engage in these parts of the economy. The project also investigated spatial, sectoral and temporal data from the Worker Registration Scheme. This showed that A8 migrants serve particular ‘functions’ in the UK, producing distinctive geographies of immigration. Explaining the uneven pattern of demand pointed to the differences, for example, between migrant labour deployed in the intensification of agricultural production and migrants used as flexible labour in construction. Analysis of the research evidence resulted in a new typology of recruitment and employment practices and a dynamic model of their spatial impacts. The research also shed light on how migrant labour is perceived and represented by UK employers. Theorisation of the knowledge practices of recruiters sheds new light on how cultural and social processes ‘produce’ and ‘reproduce’ migration geographies. This project explored labour market aspects of immigration flows , specifically A8 recruitment and employment patterns and how these changed between 2004 and the current recession. The research involved 70 interviews with labour providers (recruitment agencies) and users (employers) of migrant labour in the hospitality, food production and processing sectors across four UK study sites. This was complemented with a suite of interviews with policymakers, recruitment agencies and employers in Latvia. Since the accession of the A8 countries (Poland, Czech Republic, Latvia, Lithuania, Slovakia, Slovenia, Hungary and Estonia) to the European Union citizens from these countries have had the right to freely participate in the British labour market. As a consequence of significant disparities in earning potential, large numbers of A8 migrants have come to the UK, with nationals from these states constituting some of the largest foreign-born populations in the country. This cross-sectional (one-time) study consists of 61 transcripts from face-to-face interviews with organisations who supply (recruitment agencies) and employ (employers) in the hospitality and food production and processing sectors which were carried out across four rural and urban case study sites in England and Scotland between January and October 2010. Observation units were therefore 61 individual members of organisations that supply (recruitment companies) or use (employers) East-Central European migrant labour in the UK.

The number of people born outside of Sweden as a share of the Swedish population increased since 2010. That year, 1.38 million of the country's inhabitants were born outside of Sweden, whereas this number had increased to 2.17 million by 2023. In other words, foreign-born citizens made up around 20 percent of the population in Sweden in 2023. Of the 2.17 million people born outside of Sweden, the highest number came from Syria.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.