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.

Immigrants Admitted: Philippines data was reported at 53,287.000 Person in 2016. This records a decrease from the previous number of 56,478.000 Person for 2015. Immigrants Admitted: Philippines data is updated yearly, averaging 54,446.000 Person from Sep 1986 (Median) to 2016, with 31 observations. The data reached an all-time high of 74,606.000 Person in 2006 and a record low of 30,943.000 Person in 1999. Immigrants Admitted: Philippines data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s USA – Table US.G086: Immigration.

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.

VITAL SIGNS INDICATOR Migration (EQ4)

FULL MEASURE NAME Migration flows

LAST UPDATED December 2018

DESCRIPTION Migration refers to the movement of people from one location to another, typically crossing a county or regional boundary. Migration captures both voluntary relocation – for example, moving to another region for a better job or lower home prices – and involuntary relocation as a result of displacement. The dataset includes metropolitan area, regional, and county tables.

DATA SOURCE American Community Survey County-to-County Migration Flows 2012-2015 5-year rolling average http://www.census.gov/topics/population/migration/data/tables.All.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) Data for migration comes from the American Community Survey; county-to-county flow datasets experience a longer lag time than other standard datasets available in FactFinder. 5-year rolling average data was used for migration for all geographies, as the Census Bureau does not release 1-year annual data. Data is not available at any geography below the county level; note that flows that are relatively small on the county level are often within the margin of error. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area, in addition to the primary MSAs for the nine other major metropolitan areas, by aggregating county data based on current metropolitan area boundaries. Data prior to 2011 is not available on Vital Signs due to inconsistent Census formats and a lack of net migration statistics for prior years. Only counties with a non-negligible flow are shown in the data; all other pairs can be assumed to have zero migration.

Given that the vast majority of migration out of the region was to other counties in California, California counties were bundled into the following regions for simplicity: Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, Sonoma Central Coast: Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz Central Valley: Fresno, Kern, Kings, Madera, Merced, Tulare Los Angeles + Inland Empire: Imperial, Los Angeles, Orange, Riverside, San Bernardino, Ventura Sacramento: El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba San Diego: San Diego San Joaquin Valley: San Joaquin, Stanislaus Rural: all other counties (23)

One key limitation of the American Community Survey migration data is that it is not able to track emigration (movement of current U.S. residents to other countries). This is despite the fact that it is able to quantify immigration (movement of foreign residents to the U.S.), generally by continent of origin. Thus the Vital Signs analysis focuses primarily on net domestic migration, while still specifically citing in-migration flows from countries abroad based on data availability.

United States Immigrants Admitted: Mexico data was reported at 170,581.000 Person in 2017. This records a decrease from the previous number of 174,534.000 Person for 2016. United States Immigrants Admitted: Mexico data is updated yearly, averaging 153,629.500 Person from Sep 1986 (Median) to 2017, with 32 observations. The data reached an all-time high of 946,167.000 Person in 1991 and a record low of 66,533.000 Person in 1986. United States Immigrants Admitted: Mexico data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s USA – 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.

This layer shows children by nativity of parents by age group. This is shown by tract, county, and state boundaries. 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 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.

United States US: Net Migration data was reported at 4,500,000.000 Person in 2017. This stayed constant from the previous number of 4,500,000.000 Person for 2012. United States US: Net Migration data is updated yearly, averaging 4,213,405.500 Person from Dec 1962 (Median) to 2017, with 12 observations. The data reached an all-time high of 8,612,074.000 Person in 1997 and a record low of 1,549,465.000 Person in 1967. United States US: Net Migration data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Population and Urbanization Statistics. Net migration is the net total of migrants during the period, that is, the total number of immigrants less the annual number of emigrants, including both citizens and noncitizens. Data are five-year estimates.; ; United Nations Population Division. World Population Prospects: 2017 Revision.; Sum;

This Dataset has year-wise total number of Non-Immigrant Visas issued to Indians. It also has data related to various types of Visas issues for each year.

Note: Fiscal Year is from October to September for that respective year

The dataset consists of the number Removals by Country of Citizenship by the United State's Immigration and Customs Enforcement (ICE) in each fiscal year. An ICE removal is defined as the compulsory and confirmed movement of an inadmissible or deportable noncitizen out of the United States.

United States Immigrants Admitted: South America data was reported at 79,076.000 Person in 2017. This records a decrease from the previous number of 79,608.000 Person for 2016. United States Immigrants Admitted: South America data is updated yearly, averaging 72,183.000 Person from Sep 1986 (Median) to 2017, with 32 observations. The data reached an all-time high of 137,971.000 Person in 2006 and a record low of 41,007.000 Person in 1988. United States Immigrants Admitted: South America data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s USA – Table US.G087: Immigration.

Analysis of ‘Missing Migrants Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/jmataya/missingmigrants on 14 February 2022.

--- Dataset description provided by original source is as follows ---

About the Missing Migrants Data

This data is sourced from the International Organization for Migration. The data is part of a specific project called the Missing Migrants Project which tracks deaths of migrants, including refugees , who have gone missing along mixed migration routes worldwide. The research behind this project began with the October 2013 tragedies, when at least 368 individuals died in two shipwrecks near the Italian island of Lampedusa. Since then, Missing Migrants Project has developed into an important hub and advocacy source of information that media, researchers, and the general public access for the latest information.

Where is the data from?

Missing Migrants Project data are compiled from a variety of sources. Sources vary depending on the region and broadly include data from national authorities, such as Coast Guards and Medical Examiners; media reports; NGOs; and interviews with survivors of shipwrecks. In the Mediterranean region, data are relayed from relevant national authorities to IOM field missions, who then share it with the Missing Migrants Project team. Data are also obtained by IOM and other organizations that receive survivors at landing points in Italy and Greece. In other cases, media reports are used. IOM and UNHCR also regularly coordinate on such data to ensure consistency. Data on the U.S./Mexico border are compiled based on data from U.S. county medical examiners and sheriff’s offices, as well as media reports for deaths occurring on the Mexico side of the border. Estimates within Mexico and Central America are based primarily on media and year-end government reports. Data on the Bay of Bengal are drawn from reports by UNHCR and NGOs. In the Horn of Africa, data are obtained from media and NGOs. Data for other regions is drawn from a combination of sources, including media and grassroots organizations. In all regions, Missing Migrants Projectdata represents minimum estimates and are potentially lower than in actuality.

Updated data and visuals can be found here: https://missingmigrants.iom.int/

Who is included in Missing Migrants Project data?

IOM defines a migrant as any person who is moving or has moved across an international border or within a State away from his/her habitual place of residence, regardless of

  (1) the person’s legal status; 
  (2) whether the movement is voluntary or involuntary; 
  (3) what the causes for the movement are; or 
  (4) what the length of the stay is.[1]

Missing Migrants Project counts migrants who have died or gone missing at the external borders of states, or in the process of migration towards an international destination. The count excludes deaths that occur in immigration detention facilities, during deportation, or after forced return to a migrant’s homeland, as well as deaths more loosely connected with migrants’ irregular status, such as those resulting from labour exploitation. Migrants who die or go missing after they are established in a new home are also not included in the data, so deaths in refugee camps or housing are excluded. This approach is chosen because deaths that occur at physical borders and while en route represent a more clearly definable category, and inform what migration routes are most dangerous. Data and knowledge of the risks and vulnerabilities faced by migrants in destination countries, including death, should not be neglected, rather tracked as a distinct category.

How complete is the data on dead and missing migrants?

Data on fatalities during the migration process are challenging to collect for a number of reasons, most stemming from the irregular nature of migratory journeys on which deaths tend to occur. For one, deaths often occur in remote areas on routes chosen with the explicit aim of evading detection. Countless bodies are never found, and rarely do these deaths come to the attention of authorities or the media. Furthermore, when deaths occur at sea, frequently not all bodies are recovered - sometimes with hundreds missing from one shipwreck - and the precise number of missing is often unknown. In 2015, over 50 per cent of deaths recorded by the Missing Migrants Project refer to migrants who are presumed dead and whose bodies have not been found, mainly at sea.

Data are also challenging to collect as reporting on deaths is poor, and the data that does exist are highly scattered. Few official sources are collecting data systematically. Many counts of death rely on media as a source. Coverage can be spotty and incomplete. In addition, the involvement of criminal actors in incidents means there may be fear among survivors to report deaths and some deaths may be actively covered-up. The irregular immigration status of many migrants, and at times their families as well, also impedes reporting of missing persons or deaths.

The varying quality and comprehensiveness of data by region in attempting to estimate deaths globally may exaggerate the share of deaths that occur in some regions, while under-representing the share occurring in others.

What can be understood through this data?

The available data can give an indication of changing conditions and trends related to migration routes and the people travelling on them, which can be relevant for policy making and protection plans. Data can be useful to determine the relative risks of irregular migration routes. For example, Missing Migrants Project data show that despite the increase in migrant flows through the eastern Mediterranean in 2015, the central Mediterranean remained the more deadly route. In 2015, nearly two people died out of every 100 travellers (1.85%) crossing the Central route, as opposed to one out of every 1,000 that crossed from Turkey to Greece (0.095%). From the data, we can also get a sense of whether groups like women and children face additional vulnerabilities on migration routes.

However, it is important to note that because of the challenges in data collection for the missing and dead, basic demographic information on the deceased is rarely known. Often migrants in mixed migration flows do not carry appropriate identification. When bodies are found it may not be possible to identify them or to determine basic demographic information. In the data compiled by Missing Migrants Project, sex of the deceased is unknown in over 80% of cases. Region of origin has been determined for the majority of the deceased. Even this information is at times extrapolated based on available information – for instance if all survivors of a shipwreck are of one origin it was assumed those missing also came from the same region.

The Missing Migrants Project dataset includes coordinates for where incidents of death took place, which indicates where the risks to migrants may be highest. However, it should be noted that all coordinates are estimates.

Why collect data on missing and dead migrants?

By counting lives lost during migration, even if the result is only an informed estimate, we at least acknowledge the fact of these deaths. What before was vague and ill-defined is now a quantified tragedy that must be addressed. Politically, the availability of official data is important. The lack of political commitment at national and international levels to record and account for migrant deaths reflects and contributes to a lack of concern more broadly for the safety and well-being of migrants, including asylum-seekers. Further, it drives public apathy, ignorance, and the dehumanization of these groups.

Data are crucial to better understand the profiles of those who are most at risk and to tailor policies to better assist migrants and prevent loss of life. Ultimately, improved data should contribute to efforts to better understand the causes, both direct and indirect, of fatalities and their potential links to broader migration control policies and practices.

Counting and recording the dead can also be an initial step to encourage improved systems of identification of those who die. Identifying the dead is a moral imperative that respects and acknowledges those who have died. This process can also provide a some sense of closure for families who may otherwise be left without ever knowing the fate of missing loved ones.

Identification and tracing of the dead and missing

As mentioned above, the challenge remains to count the numbers of dead and also identify those counted. Globally, the majority of those who die during migration remain unidentified. Even in cases in which a body is found identification rates are low. Families may search for years or a lifetime to find conclusive news of their loved one. In the meantime, they may face psychological, practical, financial, and legal problems.

Ultimately Missing Migrants Project would like to see that every unidentified body, for which it is possible to recover, is adequately “managed”, analysed and tracked to ensure proper documentation, traceability and dignity. Common forensic protocols and standards should be agreed upon, and used within and between States. Furthermore, data relating to the dead and missing should be held in searchable and open databases at local, national and international levels to facilitate identification.

For more in-depth analysis and discussion of the numbers of missing and dead migrants around the world, and the challenges involved in identification and tracing, read our two reports on the issue, Fatal Journeys: Tracking Lives Lost during Migration (2014) and Fatal Journeys Volume 2, Identification and Tracing of Dead and Missing Migrants

Content

The data set records

At a time when many states are increasing restrictions on immigration, others are using formal agreements on international economic migration to open their borders. The use of international agreements on migration presents a puzzle, as most states can open their borders to migrants unilaterally. I argue that, when states cannot generate large enough flows of migrants or the right type of migrants to fill open positions in the labor market, they turn to the sending state to help them. States that need migrants can negotiate a bilateral labor agreement with a sending state, which then acts as a recruiter, helping to channel labor to the receiving state. This article details the conditions under which immigrant-receiving countries use these treaties and tests the implications of the argument on a new dataset on migration treaties.

This table contains 36 series, with data for years 1953 - 1976 (not all combinations necessarily have data for all years), and was last released on 2012-02-16. This table contains data described by the following dimensions (Not all combinations are available): Unit of measure (1 items: Persons ...) Geography (1 items: Canada ...) Origin of migrants (2 items: Overseas and the United States; Overseas ...) Intended occupations and dependents (18 items: Total immigration; Workers; managerial and administrative; Workers; professional; Total workers ...).

description: This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2006 by period of entry, region and country of origin, and state of residence. The estimates were obtained using the same residual methodology employed for estimates of the unauthorized population in 2005 (see Hoefer, Rytina and Campbell, 2006).; abstract: This report provides estimates of the number of unauthorized immigrants residing in the United States as of January 2006 by period of entry, region and country of origin, and state of residence. The estimates were obtained using the same residual methodology employed for estimates of the unauthorized population in 2005 (see Hoefer, Rytina and Campbell, 2006).

This Dataset contains year, country of citizenship, state or territory of US and gender-wise total number of permanent residents in USA

Note: Lawful permanent residents (LPRs) are foreign nationals who have been granted the right to reside permanently in the United States. LPRs are often referred to simply as "immigrants," but they are also known as "permanent resident aliens" and "green card holders."

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 ...).

Virginia has a sizable immigrant community. About 12.3 percent of the state’s residents are foreign-born, and 6.7 percent of its U.S.-born residents live with at least one immigrant parent. Immigrants make up 15.6 percent of Virginia's labor force and support the local economy in many ways. They account for 20.7 percent of entrepreneurs, 21.8 percent of STEM workers, and 12.7 percent of nurses in the state. As neighbors, business owners, taxpayers, and workers, immigrants are an integral part of Virginia’s diverse and thriving communities and make extensive contributions that benefit all.

United States Immigrants Admitted: United Kingdom data was reported at 10,948.000 Person in 2017. This records a decrease from the previous number of 12,673.000 Person for 2016. United States Immigrants Admitted: United Kingdom data is updated yearly, averaging 13,552.000 Person from Sep 1986 (Median) to 2017, with 32 observations. The data reached an all-time high of 19,973.000 Person in 1992 and a record low of 7,647.000 Person in 1999. United States Immigrants Admitted: United Kingdom data remains active status in CEIC and is reported by US Department of Homeland Security. The data is categorized under Global Database’s USA – Table US.G087: Immigration.