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.

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.

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 data shows where there are interconnections between public transportation modes at aiports, ferry, and intercity rail and bus stations in the United States. More specifically, according to the Bureau of Transportation Statistics: "The Intermodal Passenger Connectivity Database is a nationwide data table of passenger transportation terminals, with data on the availability of connections among the various scheduled public transportation modes at each facility. In addition to geographic data for each terminal, the data elements describe the availability of rail, air, bus, transit, and ferry services. This data has been collected from various public sources to provide the only nationwide measurement of the degree of connectivity available in the national passenger transportation system. At this point, data has been collected for intercity rail stations and airline airports only. Data on terminals of other modes is being collected and will be released when it is available. It is anticipated that the entire database will be complete by December 31, 2008."

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.

This dataset depicsts how ERO oversees the civil immigration detention of one of the most diverse and rapidly changing detained populations in the world. These noncitizens are housed within approximately 130 facilities across the nation.

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 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.

This dataset illustrates the largest difference between high and low temperatures and the smallest difference between high and low temperatures in cities with 50,000 people or more. A value of -1 means that the data was not applicable. Also included are the rankings, the inverse ranking to be used for mapping purposes, the popualtion, the name of city and state, and the temperature degree difference. Source City-Data URL http//www.city-data.com/top2/c489.html http//www.city-data.com/top2/c490.html Date Accessed November 13,2007

This dataset is the result of an experiment conducted in nine countries in Latin America and the Caribbean and published as the book "A Better World for Migrants in Latin America and the Caribbean". This project is joint work between the IDB and UNDP. The databases contain data collected for the impact evaluation of an intervention designed to explore which mechanisms are more effective in changing people's beliefs and attitudes toward migrants. The experiment was conducted in nine countries in Latin America and the Caribbean and consisted of two video interventions. The first video, the informative video, aimed to correct misinformation about the impact of migration by providing accurate information about the size of the migrant population and its characteristics. The second video, an emotive video, intended to appeal to the emotions and empathy of the local population.

This dataset shows the count of Deck structures per county in the United States. the count is divided into safety ratings for each county, with values from 0-9. '0' Failed '1' Imminent '2' Critical '3' Serious '4' Poor '5' Fair '6' Satisfactory '7' Good '8' Very good '9' Excellent 'Unk' Unknown 'N' Not applicable Also Dangerous is summation of 0,1,2 and 3. Risky is summation of 4, 5 and 6. Safe is summation of 7, 8 and 9. Data Source: http://www.fhwa.dot.gov/bridge/britab.htm

The U.S. Census defines Asian Americans as individuals having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent (U.S. Office of Management and Budget, 1997). As a broad racial category, Asian Americans are the fastest-growing minority group in the United States (U.S. Census Bureau, 2012). The growth rate of 42.9% in Asian Americans between 2000 and 2010 is phenomenal given that the corresponding figure for the U.S. total population is only 9.3% (see Figure 1). Currently, Asian Americans make up 5.6% of the total U.S. population and are projected to reach 10% by 2050. It is particularly notable that Asians have recently overtaken Hispanics as the largest group of new immigrants to the U.S. (Pew Research Center, 2015). The rapid growth rate and unique challenges as a new immigrant group call for a better understanding of the social and health needs of the Asian American population.

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 shows airports in the United States, Puerto Rico and the U.S. Virgin Islands. The data were derived from an extract of The Public- Use Airports database of the National Transportation Atlas Databases-2001 (NTAD-2001), published by the Bureau of Transportation Statistics, Department of Transportation. This dataset was released in October 2001 and was found on-line at the National Atlas, www.nationalatlas.gov in Shape file format. This point data is intended for use within the United States, including Puerto Rico and the U.S. Virgin Islands. This data may be used for geographic display and analysis at the national level, and for large regional areas. Metadata: http://www.nationalatlas.gov/metadata/airprtx020.faq.html Online: www.nationalatlas.gov

The United States MSA Boundaries data set contains the boundaries for metropolitan statistical areas in the United States. The data set contains information on location, identification, and size. The database includes metropolitan boundaries within all 50 states, the District of Columbia, and Puerto Rico. The general concept of a metropolitan area (MA) is one of a large population nucleus, together with adjacent communities that have a high degree of economic and social integration with that nucleus. Some MAs are defined around two or more nuclei. Each MA must contain either a place with a minimum population of 50,000 or a U.S. Census Bureau-defined urbanized area and a total MA population of at least 100,000 (75,000 in New England). An MA contains one or more central counties. An MA also may include one or more outlying counties that have close economic and social relationships with the central county. An outlying county must have a specified level of commuting to the central counties and also must meet certain standards regarding metropolitan character, such as population density, urban population, and population growth. In New England, MAs consist of groupings of cities and towns rather than whole counties. The territory, population, and housing units in MAs are referred to as "metropolitan." The metropolitan category is subdivided into "inside central city" and "outside central city." The territory, population, and housing units located outside territory designated "metropolitan" are referred to as "non-metropolitan." The metropolitan and non-metropolitan classification cuts across the other hierarchies; for example, generally there are both urban and rural territory within both metropolitan and non-metropolitan areas.

In this work, I consider public opinion and political party alignments toward immigration and trade in the United States. Despite the rising number of immigrants and the expanding volume of trade in the past several decades, the public remains skeptical of both trends. Moreover, even as partisan divisions in Congress deepen, there is little evidence of polarization at the mass level. I explore these developments by first analyzing congressional votes on the issues since the Civil War. In particular, I note how party alignments have shifted, and that Republicans are now more likely to support free trade, while Democrats are more likely to support fewer restrictions on immigration. Next, I demonstrate that polarization has in fact increased in Congress in recent years, despite public opinion surveys showing that this change has not impacted mass level attitudes. Drawing on previous distinctions in the literature, I suggest that the multidimensional nature of the issues is a contributor to this mass-elite divergence. In general, Democrats seem to be more concerned with the economic dimension of immigration, while Republicans are more concerned with its cultural impact. I solationist attitudes are a more relevant predictor of Republicans' preferences toward trade, but economic concerns are once again paramount for Democrats. Even though identifiers of both parties share similar views about the overall level of immigration and trade, they arrive at their preferences by somewhat different processes.

Projected Births by Sex, Race, and Hispanic Origin for the United States: 2016-2060 // Source: U.S. Census Bureau, Population Division // There are four projection scenarios: 1. Main series, 2. High Immigration series, 3. Low Immigration series, and 4. Zero Immigration series. // Note: Hispanic origin is considered an ethnicity, not a race. Hispanics may be of any race. All projected births are considered native born. // For detailed information about the methods used to create the population projections, see https://www2.census.gov/programs-surveys/popproj/technical-documentation/methodology/methodstatement17.pdf. // Population projections are estimates of the population for future dates. They are typically based on an estimated population consistent with the most recent decennial census and are produced using the cohort-component method. Projections illustrate possible courses of population change based on assumptions about future births, deaths, net international migration, and domestic migration. The Population Estimates and Projections Program provides additional information on its website: https://www.census.gov/programs-surveys/popproj.html.

This dataset illustrates the cities with the largest wind speed differences. Also included are the city and state, the population, the speed differnce, the ranking, and the inverse ranking (to be used only for mapping purposes). Source: City-Data URL: http://www.city-data.com/top2/c466.html Date Accessed: November 9, 2007

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.