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.

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.

In 2019, California had the highest population of unauthorized immigrants, at around 2.74 million. The overall figure for the United States was estimated to be around 11.05 million unauthorized immigrants.

As of January 2022, it was estimated that about 4.81 million illegal immigrants from Mexico were living in the United States. It was also estimated that 750,000 illegal immigrants from Guatemala were living in the United States.

This statistic shows the estimated percentage of employed undocumented immigrants in the United States in 2016, distinguished by industry. In 2017, around 14.2 percent of agriculture workers were estimated to be undocumented immigrants.

Unauthorized population estimates for 1990, 2000, and 2014.

Users can download data and reports regarding the experience of Latinos in the United States. Users can also interact with maps to view population trends over time. Background The Pew Hispanic Center website contains reports and datasets regarding the experience of Latinos in the United States. Topics include, but are not limited to: homeownership, elections, criminal justice system, and education. User Functionality Users can view and download reports. Users can also interact with maps to obtain demographic information and view population trends from 1980 to 2010. Datasets are also available to download directly into SPSS stat istical software. Surveys administered by the Pew Hispanic Center include: Hispanic Health Care Survey, National Survey of Latinos, Hispanic Religion Survey, Survey of Mexicans Living in the U.S. on Absentee Voting in Mexican Elections, Survey o f Mexican Migrants, and the Survey of Latinos on the News Media. Demographic information is available by race/ethnicity. Data Notes Report information is available on a national and county level and is indicated with the report or dataset. Demographic trends in population growth and dispersion are available for 1980 through 2010. Each report and dataset indicate years in which the data were collected and the geographic unit.

Emigration rates for border crossers during the 1990s.

This statistic shows the top ten metropolitan areas in the United States with highest unauthorized immigrant populations in 2014. With over one million unauthorized people, New York-Newark-Jersey City, NY-NJ-PA had the highest illegal immigrant population in the United States in 2014.

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 33. Aliens Apprehended: Fiscal Years 1925 to 2019 (https://www.dhs.gov/immigration-statistics/yearbook/2019/table33)

Inspiration

The data was collected to observe trends in history reflecting the number of immigrants apprehended.

Graph and download economic data for Employment Level - Foreign Born (LNU02073395) from Jan 2007 to Feb 2025 about foreign, household survey, employment, and USA.

In 2022, the greatest number of illegal aliens returned in the United States were from the Philippines, with 39,891 illegal aliens returned. India, Canada, China, and Russia rounded out the top five in that year.

The estimated population of unauthorized immigrants in the U.S. stands at around 11 million people. Although the number has stabilized, the United States has seen a spike in migrant encounters in the last few years, with over two million cases registered by the U.S. Border Patrol in 2023. This is a slight decrease from the previous year, when there were over 2.2 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, about 2.58 million illegal aliens were apprehended in the United States. This was a significant increase from the previous year, when there were around 1.87 million illegal aliens apprehended nationwide. Apprehensions refer to Border Patrol apprehensions and ICE administrative arrests.

Although teen pregnancy has been on the decline in the United States, it remains among the highest within developed countries. Hispanics, who are more likely to be undocumented immigrants, lead this trend, yet the role of legal status has yet to be considered. To investigate this question, we examine teenage fertility responses to the Deferred Action for Childhood Arrivals (DACA) program, which provides temporary legal status to undocumented youth. We find that DACA reduced the likelihood of having a teenage birth by 1.6 percentage points and eliminated roughly half of the gap in teenage childbearing between documented and undocumented women.

This statistic shows the estimated GDP loss if all illegal immigrant workers were removed from the United States. As of September 2016, the manufacturing industry would suffer an estimated 74 billion U.S. dollar decline in GDP output if all illegal immigrant workers were removed from the U.S.

Abstract

The Human Sciences Research Council (HSRC) carried out the Migration and Remittances Survey in South Africa for the World Bank in collaboration with the African Development Bank. The primary mandate of the HSRC in this project was to come up with a migration database that includes both immigrants and emigrants. The specific activities included: · A household survey with a view of producing a detailed demographic/economic database of immigrants, emigrants and non migrants · The collation and preparation of a data set based on the survey · The production of basic primary statistics for the analysis of migration and remittance behaviour in South Africa.

Like many other African countries, South Africa lacks reliable census or other data on migrants (immigrants and emigrants), and on flows of resources that accompanies movement of people. This is so because a large proportion of African immigrants are in the country undocumented. A special effort was therefore made to design a household survey that would cover sufficient numbers and proportions of immigrants, and still conform to the principles of probability sampling. The approach that was followed gives a representative picture of migration in 2 provinces, Limpopo and Gauteng, which should be reflective of migration behaviour and its impacts in South Africa.

Geographic coverage

Two provinces: Gauteng and Limpopo

Limpopo is the main corridor for migration from African countries to the north of South Africa while Gauteng is the main port of entry as it has the largest airport in Africa. Gauteng is a destination for internal and international migrants because it has three large metropolitan cities with a great economic potential and reputation for offering employment, accommodations and access to many different opportunities within a distance of 56 km. These two provinces therefore were expected to accommodate most African migrants in South Africa, co-existing with a large host population.

Analysis unit

• Household
• Individual

Universe

The target group consists of households in all communities. The survey will be conducted among metro and non-metro households. Non-metro households include those in: - small towns, - secondary cities, - peri-urban settlements and - deep rural areas. From each selected household, one adult respondent will be selected to participate in the study.

Kind of data

Sample survey data [ssd]

Sampling procedure

Migration data for South Africa are available for 2007 only at the level of local governments or municipalities from the 2007 Census; for smaller areas called "sub places" (SPs) only as recently as the 2001 census, and for the desired EAs only back so far as the Census of 1996. In sum, there was no single source that provided recent data on the five types of migrants of principal interest at the level of the Enumeration Area, which was the area for which data were needed to draw the sample since it was going to be necessary to identify migrant and non-migrant households in the sample areas in order to oversample those with migrants for interview.

In an attempt to overcome the data limitations referred to above, it was necessary to adopt a novel approach to the design of the sample for the World Bank's household migration survey in South Africa, to identify EAs with a high probability of finding immigrants and those with a low probability. This required the combined use of the three sources of data described above. The starting point was the CS 2007 survey, which provided data on migration at a local government level, classifying each local government cluster in terms of migration level, taking into account the types of migrants identified. The researchers then spatially zoomed in from these clusters to the so-called sub-places (SPs) from the 2001 Census to classifying SP clusters by migration level. Finally, the 1996 Census data were used to zoom in even further down to the EA level, using the 1996 census data on migration levels of various typed, to identify the final level of clusters for the survey, namely the spatially small EAs (each typically containing about 200 households, and hence amenable to the listing operation in the field).

A higher score or weight was attached to the 2007 Community Survey municipality-level (MN) data than to the Census 2001 sub-place (SP) data, which in turn was given a greater weight than the 1996 enumerator area (EA) data. The latter was derived exclusively from the Census 1996 EA data, but has then been reallocated to the 2001 EAs proportional to geographical size. Although these weights are purely arbitrary since it was composed from different sources, they give an indication of the relevant importance attached to the different migrant categories. These weighted migrant proportions (secondary strata), therefore constituted the second level of clusters for sampling purposes.

In addition, a system of weighting or scoring the different persons by migrant type was applied to ensure that the likelihood of finding migrants would be optimised. As part of this procedure, recent migrants (who had migrated in the preceding five years) received a higher score than lifetime migrants (who had not migrated during the preceding five years). Similarly, a higher score was attached to international immigrants (both recent and lifetime, who had come to SA from abroad) than to internal migrants (who had only moved within SA's borders). A greater weight also applied to inter-provincial (internal) than to intra-provincial migrants (who only moved within the same South African province).

How the three data sources were combined to provide overall scores for EA can be briefly described. First, in each of the two provinces, all local government units were given migration scores according to the numbers or relative proportions of the population classified in the various categories of migrants (with non-migrants given a score of 1.0. Migrants were assigned higher scores according to their priority, with international migrants given higher scores than internal migrants and recent migrants higher scores than lifetime migrants. Then within the local governments, sub-places were assigned scores assigned on the basis of inter vs. intra-provincial migrants using the 2001 census data. Each SP area in a local government was thus assigned a value which was the product of its local government score (the same for all SPs in the local government) and its own SP score. The third and final stage was to develop relative migration scores for all the EAs from the 1996 census by similarly weighting the proportions of migrants (and non-migrants, assigned always 1.0) of each type. The the final migration score for an EA is the product of its own EA score from 1996, the SP score of which it is a part (assigned to all the EAs within the SP), and the local government score from the 2007 survey.

Based on all the above principles the set of weights or scores was developed.

In sum, we multiplied the proportion of populations of each migrant type, or their incidence, by the appropriate final corresponding EA scores for persons of each type in the EA (based on multiplying the three weights together), to obtain the overall score for each EA. This takes into account the distribution of persons in the EA according to migration status in 1996, the SP score of the EA in 2001, and the local government score (in which the EA is located) from 2007. Finally, all EAs in each province were then classified into quartiles, prior to sampling from the quartiles.

From the EAs so classified, the sampling took the form of selecting EAs, i.e., primary sampling units (PSUs, which in this case are also Ultimate Sampling Units, since this is a single stage sample), according to their classification into quartiles. The proportions selected from each quartile are based on the range of EA-level scores which are assumed to reflect weighted probabilities of finding desired migrants in each EA. To enhance the likelihood of finding migrants, much higher proportions of EAs were selected into the sample from the quartiles with the higher scores compared to the lower scores (disproportionate sampling). The decision on the most appropriate categorisations was informed by the observed migration levels in the two provinces of the study area during 2007, 2001 and 1996, analysed at the lowest spatial level for which migration data was available in each case.

Because of the differences in their characteristics it was decided that the provinces of Gauteng and Limpopo should each be regarded as an explicit stratum for sampling purposes. These two provinces therefore represented the primary explicit strata. It was decided to select an equal number of EAs from these two primary strata.

The migration-level categories referred to above were treated as secondary explicit strata to ensure optimal coverage of each in the sample. The distribution of migration levels was then used to draw EAs in such a way that greater preference could be given to areas with higher proportions of migrants in general, but especially immigrants (note the relative scores assigned to each type of person above). The proportion of EAs selected into the sample from the quartiles draws upon the relative mean weighted migrant scores (referred to as proportions) found below the table, but this is a coincidence and not necessary, as any disproportionate sampling of EAs from the quartiles could be done, since it would be rectified in the weighting at the end for the analysis.

The resultant proportions of migrants then led to the following proportional allocation of sampled EAs (Quartile 1: 5 per cent (instead of 25% as in an equal distribution), Quartile 2: 15 per cent (instead

In 2022, the greatest number of illegal aliens apprehended in the United States were from Mexico, with 836,844 illegal aliens apprehended. Guatemala, Cuba, Honduras, and Venezuela rounded out the top five in that year.

As of 2023, 27.3 percent of California's population were born in a country other than the United States. New Jersey, New York, Florida, and Nevada rounded out the top five states with the largest population of foreign born residents in that year. For the country as a whole, 14.3 percent of residents were foreign born.