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.

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 ...).

This Dataset contains year and country wise Nonimmigrant Visas issued by USA to citizens of other nations

Public use data set on new legal immigrants to the U.S. that can address scientific and policy questions about migration behavior and the impacts of migration. A survey pilot project, the NIS-P, was carried out in 1996 to inform the fielding and design of the full NIS. Baseline interviews were ultimately conducted with 1,127 adult immigrants. Sample members were interviewed at baseline, 6 months, and 12 months, with half of the sample also interviewed at three months. The first full cohort, NIS-2003, is based on a nationally representative sample of the electronic administrative records compiled for new immigrants by the US government. NIS-2003 sampled immigrants in the period May-November 2003. The geographic sampling design takes advantage of the natural clustering of immigrants. It includes all top 85 Metropolitan Statistical Areas (MSAs) and all top 38 counties, plus a random sample of other MSAs and counties. Interviews were conducted in respondents'' preferred languages. The baseline was multi-modal: 60% of adult interviews were administered by telephone; 40% were in-person. The baseline round was in the field from June 2003 to June 2004, and includes in the Adult Sample 8,573 respondents, 4,336 spouses, and 1,072 children aged 8-12. A follow-up was planned for 2007. Several modules of the NIS were designed to replicate sections of the continuing surveys of the US population that provide a natural comparison group. Questionnaire topics include Health (self-reports of conditions, symptoms, functional status, smoking and drinking history) and use/source/costs of health care services, depression, pain; background; (2) Background: Childhood history and living conditions, education, migration history, marital history, military history, fertility history, language skills, employment history in the US and foreign countries, social networks, religion; Family: Rosters of all children; for each, demographic attributes, education, current work status, migration, marital status and children; for some, summary indicators of childhood and current health, language ability; Economic: Sources and amounts of income, including wages, pensions, and government subsidies; type, value of assets and debts, financial assistance given/received to/from respondent from/to relatives, friends, employer, type of housing and ownership of consumable durables. * Dates of Study: 2003-2007 * Study Features: Longitudinal * Sample Size: 13,981

The main dataset ("ESB Mobility Database") contains occupational data on 1,200 Irish immigrants who arrived in the U.S. in the Famine years and could be tracked for at least a decade. We also present the most up-to-date version of our Emigrant Savings Bank Depositor Database, which contains data on all 15,000 people who opened accounts at the bank from 1850 to 1858. Also provided are data from the 1855 New York State census documenting the occupations of New York's entire Irish-born population as well as datasets documenting the occupations held by New York's Irish immigrants one year and ten years after their arrival in America,

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

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 ...).

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.

Acknowledgement

The following table is imported from the 2019 Yearbook of Immigration Statistics under the Department of Homeland Security:

The 2019 Yearbook of Immigration Statistics is a compendium of tables that provide data on foreign nationals who are granted lawful permanent residence (i.e., immigrants who receive a “green card”), admitted as temporary nonimmigrants, granted asylum or refugee status, or are naturalized. The Yearbook also presents data on immigration enforcement actions, including apprehensions and arrests, removals, and returns.

Table 39. Aliens Removed or Returned: Fiscal Years 1892 to 2019 (https://www.dhs.gov/immigration-statistics/yearbook/2019/table39)

Inspiration

The data was collected to observe trends in history reflecting the number of immigrants deported - more specifically removed or returned.

The dissertation consists of three chapters relating to the measurement of immigration policies, which developed out of my work as an initial co-author of the International Migration Policy and Law Analysis (IMPALA) Database Project. The first chapter entitled, “Brain Gain? Measuring skill bias in U.S. migrant admissions policy,” develops a conceptual and operational definition of skill bias. I apply the measure to new data revealing the level of skill bias in U.S. migrant admissions policy between 1965 and 2008. Skill bias in U.S. migrant admissions policy is both a critical determinant of the skill composition of the migrant population and a response to economic and public demand for highly skilled migrants. However, despite its central role, this is the first direct, comprehensive, annual measure of skill bias in U.S. migrant admissions policy. The second chapter entitled, “Stalled in the Senate: Explaining change in US migrant admissions policy since 1965,” presents new data characterizing change in U.S. migrant admissions policy as both expansive and infrequent over recent decades. I present a new theory of policy change in U.S. migrant admissions policy that incorporates the role of supermajoritarian decision making procedures and organized anti-immigration groups to better account for both the expansive nature and t he infrequency of policy change. The theory highlights the importance of a coalition of immigrant advocacy groups, employers and unions in achieving policy change and identifies the conditions under which this coalition is most likely to form and least likely to be blocked by an anti-immigration group opposition. The third chapter entitled, “Post-coding aggregation: A methodological principle for independent data collection,” presents a new technique developed to enable independent collection of flexible, high quality data: post-coding aggregation. Post-coding aggregation is a methodological principle that minimizes data loss, increases transparency, and grants data analysts the ability to decide how best to aggregate information to produce measures. I demonstrate how it increases the fl exibility of data use by expanding the utility of data collections for a wider range of research objectives and improves the reliability and the content validity of measures in data analysis.

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.

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.

This dataset provides detailed information on the issuance of non-immigrant visas in the United States in 2022, categorized by visa category and nationality of applicants. The data comes from official statistics of the United States Department of State.

Data source: Data are extracted from annual reports published by the U.S. Department of State.

Variables included: Nationality: The nationality of visa applicants.

Use: This data can be used to analyze trends in the issuance of nonimmigrant visas in the United States, understand the distribution of visas by nationality, and evaluate U.S. immigration policies.

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.

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."

Facts and Figures 2016: Immigration Overview – Permanent Residents presents the annual intake of permanent residents by category of immigration from 2007 to 2016. The main body of the publication consists of a series of statistical tables and charts covering the ten-year period from 2007 to 2016. The report depicts selected characteristics for permanent residents.

The statistics for admission of permanent residents are provided for the three main categories of immigration—family class, economic immigrants and refugees—as well as for other immigrants who do not qualify in any of these categories.

This research adds to the expanding field of data-driven analysis, scientific modeling, and forecasting on the impact of having access to the Internet and IoT on the general US population regarding immigrants and immigration policies. More specifically, this research focuses on the public opinion of undocumented immigrants in the United States and having access to the Internet in their local settings. The term Undocumented Immigrants refers to those who live in the United States without legal papers, documents, or visas. Undocumented immigrants may have come into the country unlawfully or with valid documentation, but their legal status has expired. Using the 2020 American National Election Studies (ANES) time series dataset, I investigated the relationship between internet access (A2I) and public perception of undocumented immigrants. According to my research and analysis, increasing internet access among non-Hispanic whites with at least a bachelors degree with an annual household income of less than 99K is more likely to oppose the deportation of undocumented immigrants and separating unaccompanied children from their families in borderland areas. The individuals with substantial Republican political ideology exhibit significantly lower opposing effects in deporting undocumented immigrants or separating unaccompanied children from their families. The evidence from multiple statistical models is resilient to a variety of factors. The findings show that increased internet access may improve undocumented immigrants social integration and acceptability. During health emergencies, it may be especially beneficial to make them feel safe, included, and supported in their local settings.