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.

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.

This dataset provides values for INTERNATIONAL MIGRANT STOCK PERCENT OF POPULATION WB DATA.HTMLES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Abstract

This dataset, a product of the Trade Team - Development Research Group, is part of a larger effort in the group to measure the extent of the brain drain as part of the International Migration and Development Program. It measures international skilled migration for the years 1975-2000.

The methodology is explained in: "Tendance de long terme des migrations internationals. Analyse à partir des 6 principaux pays recerveurs", Cécily Defoort.

This data set uses the same methodology as used in the Docquier-Marfouk data set on international migration by educational attainment. The authors use data from 6 key receiving countries in the OECD: Australia, Canada, France, Germany, the UK and the US.

It is estimated that the data represent approximately 77 percent of the world’s migrant population.

Bilateral brain drain rates are estimated based observations for every five years, during the period 1975-2000.

Geographic coverage

Australia, Canada, France, Germany, UK and US

Kind of data

Aggregate data [agg]

Mode of data collection

Other [oth]

Since its inception, the DHS has produced Fiscal Yearly ERO and detention statistics reports that provide information on detention and Alternatives to Detention (ATD) statistics. This dataset compiles the Ice Detention Data, Average in Custody Length of Stay (ICLOS) and Detainees, and Facilities tabs of the FY19, FY20, FY21, and FY22 DHS-ICE reports (referenced below), into a multi-year dataset.

Data Clean-up Process: To assist in the analysis and clear understanding of the data, and fix inaccuracies and data silences in the original data, additional columns were added to the facilities tab. Additionally, columns that were not used in the analysis and where outside of the scope of work, were removed from the new dataset. Rationale for the additional columns and the columns removed is as follow:

New Operator Category column: In attempting to understand the type of DHS facilities and how they may have changed through the years, an Operator Category column was added, where every facility is categorized as A) Country or City Facility (public), B) Privately Operated Facility, and C) Unknown operator. New Gender Modified Column: Upon reviewing the total number of female and male detainees for each facility it was noted that the original Male/Female column, which categorized each facility by the gender of the detainees, was often not reflective of the detainee population. To fix this error, a new "Gender Modified" column was added and the facilities were categorized as A) Male, B) Female, and C) Female and Male depending on the Total Male and Total Female columns of the reports. The new Gender Modified column is based on the ADP numbers of female vs. male detainees. If there were 0 female detainees, the facility was categorized as Male. If there were 0 Male ADP detainees, the facility was categorized as Female. If there were 1 or more detainees for both the female and male totals, the facility was categorized as Female and Male. New FY19-22 Active columns and New Ice Facilities ACTIVE 19-22 tab: Since the project attempts to do a multi-year analysis, five new columns were added to indicate if a facility was active FY19-22, Active FY19, Active FY20, Active FY21, and Active FY22. A facility that was active in a particular year was marked as Y. A facility that was Active all four years was marked as Y in the Active FY19-22 column. Certain modeling and hypothesis testing methodologies required that only the statistics for the facilities that were active FY19-22 be used. For this purpose, a second Tab named “Ice Facilities ACTIVE 19-22” was created. Removal of second to last inspection columns: The original DHS reports included additional columns with second to last inspection type, standard, and date. For the scope of this project, these columns were removed from each year and only the Last Inspection type, standard, and date were left and used for this project. New Percentage of Criminality columns: To calculate the percentage of criminality among detainees new Percentage of Criminality columns were added for each fiscal year. The percentages were calculated by the formula: (ADP: Criminality: Male Crim + ADP: Criminality: Female Crim) / (ADP Total Male + FY: Total Female) NA cells: to indicate that no information was provided by ICE in the original reports or to indicate that the particular facility was not active for a particular year, NA was added in the corresponding cells. Additional data analysis in R changed the NA to nulls.

This paper studies the impact of immigration to the United States on the vote share for the Republican Party using county-level data from 1990 to 2016. Our main contribution is to show that an increase in high-skilled immigrants decreases the share of Republican votes, while an inflow of low-skilled immigrants increases it. These effects are mainly due to the indirect impact on existing citizens' votes and this is independent of the origin country and race of immigrants. We find that the political effect of immigration is heterogeneous across counties and depends on their skill level, public spending and non-economic characteristics.

Data and code for peer-reviewed article published in American Economic Journal: Applied Economics. When citing this dataset, please also cite the associated article. A sample Publication Citation is provided below.

a Includes Costa Rica, Dominican Republic, Guatemala and Panamab Adjusted for infant sex, maternal age groups (

Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows six condensed maps of Canada. Following those of British and French origin, the next most numerous groups in 1951 were those of German (619,995); Ukrainian (395,043); Scandinavian (283,024); Netherlands (264,267); Polish (219,854); and Jewish (181,670) origin. The three maps on the left of this plate show the population distribution of the aforementioned groups. For each group, the percentage distribution of population for provinces and territories is also provided by means of a pie chart. The three maps on the right of this plate are concerned with citizenship and immigration and show the percentage of persons born in Canada to the total population, the percentage of immigrants to the total population and the percentage of Canadian citizens to the total population.

Description of parameters.

Do discriminatory U.S. immigration policies affect foreign public opinion about Americans? When examining negative reactions to U.S. actions perceived as bullying on the world stage, existing research has focused either on U.S. policies that involve direct foreign military intervention or seek to influence foreign countries' domestic economic policy or policies advocating minority representation. We argue that U.S. immigration policies—especially when they are perceived as discriminatory—can similarly generate anti-American sentiment. Using data from a conjoint experiment embedded in a unique survey of Nigerian expatriates in Ghana in the field before and after President Trump surprisingly announced a ban on Nigerian immigration to the United States, we estimate a large 13 percentage point drop in Nigerian subjects' favorability towards American citizens.