United States Immigrants Admitted: All Countries data was reported at 1,127,167.000 Person in 2017. This records a decrease from the previous number of 1,183,505.000 Person for 2016. United States Immigrants Admitted: All Countries data is updated yearly, averaging 451,510.000 Person from Sep 1900 (Median) to 2017, with 118 observations. The data reached an all-time high of 1,827,167.000 Person in 1991 and a record low of 23,068.000 Person in 1933. United States Immigrants Admitted: All Countries data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s United States – Table US.G087: Immigration.

In January 2022, it was estimated that about 1.85 million male illegal immigrants living in the United States were aged between 35 and 44 years old. In that same year, it was estimated that 1.52 million female illegal immigrants living in the U.S. were between 35 and 44 years old.

The estimated population of unauthorized immigrants in the U.S. stands at around ** million people. Although the number has stabilized, the United States has seen a spike in migrant encounters in the last few years, with over * million cases registered by the U.S. Border Patrol in 2023. This is a slight decrease from the previous year, when there were over *** million cases registered. Due to its proximity and shared border, Mexico remains the leading country of origin for most undocumented immigrants in the U.S., with California and Texas being home to the majority.

Immigration and political division

Despite the majority of the population having immigrant roots, the topic of immigration in the U.S. remains one of the country’s longest-standing political debates. Support among Republicans for restrictive immigration has grown alongside Democratic support for open immigration. This growing divide has deepened the polarization between the two major political parties, stifling constructive dialogue and impeding meaningful reform efforts and as a result, has led to dissatisfaction from all sides. In addition to general immigration policy, feelings toward illegal immigration in the U.S. also vary widely. For some, it's seen as a significant threat to national security, cultural identity, and economic stability. This perspective often aligns with support for stringent measures like Trump's proposed border wall and increased enforcement efforts. On the other hand, there are those who are more sympathetic toward undocumented immigrants, as demonstrated by support for the Deferred Action for Childhood Arrivals (DACA) program.

In 2022, an estimated 10.99 million unauthorized immigrants were living in the United States. This is an increase from about 3.5 million unauthorized immigrants who lived in the United States in 1990.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows children by nativity of parents by age group. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of children who are in immigrant families (children who are foreign born or live with at least one parent who is foreign born). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B05009 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 11, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Historical migration from Africa to the United States is a delicate and complex issue. Although African-Americans make up more than one eighth of the current US population, the majority of their ancestors would most likely trace back to chattel slavery, which was prevalent throughout the Americas from the sixteenth to the nineteenth century. Although the slave trade was abolished in the US in 1808, illegal smuggling continued for years after (particularly from the Caribbean, as it was not abolished throughout the British Empire until 1833), and the practice of slavery continued until 1865. Another noteworthy point to remember is that the term "African-American" is generally applied to those with Sub-Saharan roots, and not to those from the predominantly Arabic, North Africa.

The data shown here applies only to free, documented migrants from the continent of Africa to the United States, between 1820 and 1957. In the nineteenth century, migration from Africa to the US was very low, and it was rare that more than one hundred migrants arrived in the US in any given year. Migration did increase in the first half of the twentieth century, however it was still the lowest out of all continents, including Oceania, which had a much lower overall population than Africa.

There is a large econometric literature that examines the economic assimilation of immigrants in the United States and elsewhere. On the whole immigrants are seen as atomistic individuals assimilating in a largely anonymous labour market, a view that runs counter to the spirit of the equally large literature on ethnic groups. Here we argue that immigrants assimilate as communities, not just as individuals. The longer the immigrant community has been established the better adjusted it is to the host society and the more the host society comes to accept that ethnic group. Thus economic outcomes for immigrants should depend not just on their own characteristics, but also on the legacy of past immigration from the same country. In this paper we test this hypothesis using data from a 5 percent sample of the 1980, 1990 and 2000 US censuses. We find that history matters in immigrant assimilation: the stronger is the tradition of immigration from a given source country, the better the economic outcomes for new immigrants from that source.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study is an analysis of 13 waves of data retrieved from the National Longitudinal Survey of Youth 1997 survey (NLSY97) in order to examine the influence of marriage on immigrant offending trajectories from adolescence to young adulthood. There were three specific research questions considered: Are second generation immigrants entering into marriage at a slower pace than their first generation immigrant peers? What role does marriage play in understanding immigrant offending? Is the relationship between marriage and offending affected by immigrant generation or country/region of birth (i.e., nativity)? Distributed here is the code used for the secondary analysis and the code to compile the datasets.

The United States hosted, by far, the highest number of immigrants in the world in 2024. That year, there were over ** million people born outside of the States residing in the country. Germany and Saudi Arabia followed behind at around **** and **** million, respectively. There are varying reasons for people to emigrate from their country of origin, from poverty and unemployment to war and persecution. American Migration People migrate to the United States for a variety of reasons, from job and educational opportunities to family reunification. Overall, in 2021, most people that became legal residents of the United States did so for family reunification purposes, totaling ******* people that year. An additional ******* people became legal residents through employment opportunities. In terms of naturalized citizenship, ******* people from Mexico became naturalized American citizens in 2021, followed by people from India, the Philippines, Cuba, and China. German Migration Behind the United States, Germany also has a significant migrant population. Migration to Germany increased during the mid-2010's, in light of the Syrian Civil War and refugee crisis, and during the 2020’s, in light of conflict in Afghanistan and Ukraine. Moreover, as German society continues to age, there are less workers in the labor market. In a low-migration scenario, Germany will have **** million skilled workers by 2040, compared to **** million by 2040 in a high-migration scenario. In both scenarios, this is still a decrease from **** skilled workers in 2020.

People who have been granted permanent resident status in Canada. Please note that in these datasets, the figures have been suppressed or rounded to prevent the identification of individuals when the datasets are compiled and compared with other publicly available statistics. Values between 0 and 5 are shown as “--“ and all other values are rounded to the nearest multiple of 5. This may result to the sum of the figures not equating to the totals indicated.

This paper demonstrates the effect of country level corruption on illicit behavior of individuals in a foreign country. The empirical research investigates the probability of individuals being apprehended overseas due to the influence of corrupt environment in their home countries. Using cross-sectional data for empirical analysis from 104 different countries over the period of 2009– 2011, the authors focused on finding how people from various countries act and behave differently while stationing outside of their home countries. Their findings reveal some evidences that individuals coming to the United States from corruption-ridden countries are more likely to be apprehended than individuals from less corrupt countries are.

How will worldwide changes in population affect pressures for international migration in the future? We examine the past three decades, during which population pressures contributed to substantial labor flows from neighboring countries into the United States and Europe, and contrast them with the coming three decades, which will see sharp reductions in labor-supply growth in Latin America but not in Africa or much of the Middle East. Using a gravity-style empirical model, we examine the contribution of changes in relative labor-supply to bilateral migration in the 2000s and then apply this model to project future bilateral flows based on long-run UN forecasts of working-age populations in sending and receiving countries. Because the Americas are entering an era of uniformly low population growth, labor flows across the Rio Grande are projected to slow markedly. Europe, in contrast, will face substantial demographically driven migration pressures from across the Mediterranean for decades to come. Although these projected inflows would triple the first-generation immigrant stocks of larger European countries between 2010 and 2040, they would still absorb only a small fraction of the 800-million-person increase in the working-age population of Sub-Saharan Africa that is projected to occur over this period.

Many U.S.-born descendants of Mexican immigrants do not identify as Mexican or Hispanic in response to the Hispanic origin question asked in the Census and other government surveys. Analyzing microdata from the 2000 U.S. Census and the 2001-2019 American Community Surveys, we show that the age at arrival of Mexican immigrants exerts an important influence on ethnic identification not only for these immigrants themselves but also for their U.S.-born children. Among Mexican immigrants who arrived as children, the rate of “ethnic attrition”—i.e., not self-identifying as Mexican or Hispanic—is higher for those who migrated at a younger age. Moreover, the children of these immigrants exhibit a similar pattern: greater ethnic attrition among children whose parents moved to the United States at a younger age. We unpack the relative importance of several key mechanisms—parental English proficiency, parental education, family structure, intermarriage, and geographic location—through which the age at arrival of immigrant parents influences the ethnic identification of their children. Intermarriage turns out to be the primary mechanism: Mexican immigrants who arrived at a very young age are more likely to marry non-Hispanics, and the rate of ethnic attrition is dramatically higher among children with mixed ethnic backgrounds. Prior research demonstrates that arriving at an early age hastens and furthers the integration of immigrants. We show here that this pattern also holds for ethnic identification and that the resulting differences in ethnic attrition among first-generation immigrants are transmitted to their second-generation children.

This layer shows children by nativity of parents by age group. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the count and percentage of children who are in immigrant families (children who are foreign born or live with at least one parent who is foreign born). To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B05009Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

Canada’s appeal as an immigration destination has been increasing over the past two decades, with a total of 464,265 people immigrating to the country in 2024. This figure is an increase from 2000-2001, when approximately 252,527 immigrants came to Canada. Immigration to the Great White North Between July 1, 2022 and June 30, 2023, there were an estimated 199,297 immigrants to Ontario, making it the most popular immigration destination out of any province. While the number of immigrants has been increasing over the years, in 2024 over half of surveyed Canadians believed that there were too many immigrants in the country. However, in 2017, the Canadian government announced its aim to significantly increase the number of permanent residents to Canada in order to combat an aging workforce and the decline of working-age adults. Profiles of immigrants to Canada The gender of immigrants to Canada in 2023 was just about an even split, with 234,279 male immigrants and 234,538 female immigrants. In addition, most foreign-born individuals in Canada came from India, followed by China and the Philippines. The United States was the fifth most common origin country for foreign-born residents in Canada.

Immigration to this country has increased significantly in recent years. While Mexican immigrants are the largest population of immigrants in the United States (39 percent), the rest of the population is widely varied, with no one nation accounting for more than 3 percent of all immigrants. Despite the significant benefits quality Early Childhood Education (ECE) programs offer to immigrant children, their rates of enrollment are significantly lower than for comparable children of United States-born parents. In order to better address the needs of these new American families, providers and state policymakers need more in-depth knowledge about the perceptions of these families and the factors that influence their choice of care. This study is an exploratory study in two cities which reflect the diversity of experience with immigration across the country: Denver, Colorado and surrounding areas, where the focus is on Mexican immigrants, and Portland, Maine and surrounding areas, where the focus is on three of the many refugee populations which have newly settled here. The contrasts, not only in the immigrant populations themselves, but also in the political and historical contexts of the communities in which they live, offer an opportunity to enrich the field of research on child care choices for this vulnerable population of children and families.Additional details about this study can be found on the New Americans Web site.

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 ...).