Illegal Immigrants in High Income Countries and Politically Autonomous Units: Recent Estimated Stocks by Country and Unit


Illegal Immigrants in High Income Countries and Politically Autonomous Units: Recent Estimated Stocks by Country and Unit
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Author: Reuveny, Rafael
Journal: Journal of Globalization Studies. Volume 7, Number 1 / May 2016

This paper estimates stocks of illegal immigrants currently residing in the high income world by country and politically autonomous unit (PAU). The estimates either come as such from sources or are computed here based on auxiliary data. All the computations and sources are documented. The current version suggests the number of illegal immigrants currently residing in the high income world could be as high as 42.4 million. I provide the database in the form of an Excel file. I treat this project as an ongoing effort and invite other scholars to alter or amend it in future research.

Keywords: Dataset, Excel format, Documentation, Multiple Sources

Results and calculations

Approach

This paper estimates stocks of illegal immigrants currently residing in the high income world, by country and politically autonomous unit (PAU). I provide results and calculations in an accompanying Excel file with four sheets (can be downloaded from the electronic version of this paper at http://www.sociostudies.org/journal/articles/450866/). The sheet entitled ‘High Income Countries and PAUs’ includes estimates and auxiliary computations. The sheets entitled ‘Croatia’, ‘Latvia’, ‘Finland’, and ‘GCC countries’ (GCC stands for the Gulf Cooperation Council) provide computations for these particular cases.

The Excel file cites the source of each numerical input, the full details of which are provided in the end of this paper. In what follows, I discuss how the estimates are obtained. My goal was to compile and utilize available data, rather than to make any judgment about their quality as other researchers have done (e.g., Clandestino 2009). Since the nature of illegal immigration necessitates secrecy on the part of those involved, I find it nearly impossible to judge the quality of such estimates; even the clearest and most logical procedure prepared by the best country expert with full access to official data must be less than perfectly accurate.

I identify high income countries and PAUs based on a World Bank report (WB 2011). World Bank (2013a) defines high income in 2012 as a Gross National Income per capita (GNIpc) of at least $12,616. The World Bank excludes Taiwan (World Bank 2013b), probably due to its sensitivity vis-à-vis China. I include Taiwan here since it operates as a country and currently has a GNIpc of $20,910 (World Bank 2013c). The PAUs come in two types: (1) China's Special Administrative Regions of Macau and Hong Kong, and (2) Overseas Territories linked with former colonial powers (e.g., Puerto Rico, the Netherlands Antilles). PAUs essentially run their own immigration and socioeconomic policies and their residents may have easier entry as immigrants to their mother country. I do not address this issue here.

Sources and Estimates

The data come from media outlets, practitioners, institutions, governments, and academics. The media outlets are mostly newspapers, while the practitioners include non-profits, philanthropic bodies, think tanks, and consulting agencies. The institutions include the International Labour Organization, the Organization for Economic Development and Cooperation (OECD), the International Organization of Migration, the European Commission and others. The government sources are exclusively official papers, and the academic sources are journal articles, books, and book chapters. A variety of counts are used, including expired non-departing visas, people captured illegally working or crossing borders, and illegal residents arrested for various crimes. Some reports hint their sources wish to remain unidentified or rely on surveys of anonymous employers and foreigners, while others do not explicate their method.1

Most sources offer a range of estimates, recognizing the inherent uncertainty. I list several ranges by place with their mean low and high ends. When a range is not offered, I use the same number for both sides. The means are used to compute totals across all the places, for each side of the range. Graphically, the range for this total (or for any database entry) resides within a larger range stretching from the smallest to the largest estimate found, as shown below. The mean stock of illegal immigrants is between X and Y, and the stock itself could be as small as W and as large as Z.

Smallest estimate

Minimum mean

Maximum mean

Largest estimate

W

X

Y

Z

|--------------------------|--------------------------|--------------------------|

Auxiliary Calculations

Most of the estimates come directly from original sources. I compute other estimates. The phrase ‘For A, B…’ below applies to some estimates for countries A, B…, not to all their estimates, as in almost all cases, some estimates are original, and in several cases I use more than one estimation method.

For Belgium, Cyprus, Equatorial Guinea (EG), France, Germany, Italy, Japan, Luxembourg, the Netherlands, Singapore, Spain, Switzerland, UAE, and the United Kingdom, estimates report shares of illegal immigrants in the legal population. I applied these shares to the current population from World Bank (2013d), yielding a total estimate assuming the illegal and the legal groups grow at the same rate.

For Greece and Italy, I used the reported share of the illegal immigrant population in the total (illegal + legal) population (n) to solve for the stock of illegal immigrants (z) based on the current stock of the legal residents (L). I begin with and get

For Australia and New Zealand, I used the reported share of the illegal immigrant stock in the total (illegal + legal) immigrant stock to find z above, with L now the legal immigrant stock.

For Denmark, Ireland, Aruba, and South Korea, I applied the reported share of illegal immigrants in the legal immigrant stock, to the legal immigrant stock in World Bank (2013e).

For the next two groups, I used stocks of illegal foreign workers as proxies for stocks of illegal migrants. Notably, these proxies may be too small if these workers have with them nonworking family members (e.g., children, spouses, and extended family); I was largely unable to find data addressing this problem. For Austria, Greece, Italy, Switzerland, and the US, I applied the reported share of illegal workers in the total legal population to the total legal population. For Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and UAE I used the reported share of illegal immigrants in the total workforce (illegal + legal) to compute the illegal immigrant stock z above, with L now the total legal workforce.

For Kuwait and the UAE, I found stocks of illegal immigrants and Biduns (Arabic, without nationality; also Bedoun, Bidoon, and Bedoon). Formerly from nomadic tribes, Arab nations, or Iran, the Kuwaiti government calls them illegal residents (Right Now, 2012). They have limited or no access to state resources, including healthcare. I list estimates with and without Biduns.

For Qatar, Saudi Arabia, and UAE, I found estimates for the share of the illegal immigrants in the migrant workforce (ISW), the total workforce (legal immigrants + nationals) (WF), and the legal migrant share of this workforce (MS). The illegal migrants stock is given by which also may undervalue the illegal migrant stock, since it does not count any nonworking resident family members.

For Hungary, I found data for WF (above), share of undeclared workforce in the total workforce (legal immigrants + nationals) (USW), and share of undeclared immigrant labor in the undeclared workforce (USM). Assuming the undeclared immigrant labor consists of illegal immigrants, the illegal migrant workforce is given by.

For Australia and South Korea, I use the share of illegal immigrants in the total immigrant stock (legal + illegal) (n) and the total legal immigrant stock (L). The illegal immigrant stock is given by

For South Korea, I add the stocks of illegal immigrant workers (IW), school-aged children of illegal workers (IC), and mothers of these children (IM) to get the illegal immigrant stock. This computation assumes that the mothers do not work and does not account for any illegal immigrant who is a nonworking non-mother or any child younger than school-aged.

For Ireland, there are data on the stock of illegal immigrant workers (IW), share of married illegal immigrant workers (SM), share of the latter with non-working spouses present in Ireland (MP), share of illegal immigrant workers with children (SC), and share of the latter with non-working children present in Ireland (CP). I compute the illegal immigrant stock by. This estimate may undervalue the true number, for it accounts for only one nonworking child per family.

For Guam, I found estimates of the illegal immigrant stock in 1997 (z1997) and the average yearly number of illegal immigrants (flow). The source is not clear on whether flow applies since 1997 or 2000, so I provide estimates for both. The illegal immigrant stock is computed by, where T is 14 (2000 to 2013) or 17 (1997 to 2013). This computation may overvalue the true number, for it does not account for those who left Guam or died since 1997.

For Japan, there are data for uncaptured migrants overstaying their visa and people who entered the country illegally. The two numbers are added here to estimate the illegal stock.

For Croatia, there are data on yearly apprehensions while crossing borders illegally, yearly apprehensions of foreigners working illegally, and share of illegal immigrants in the legal immigrant stock. I create three estimates: (1) sum the yearly border apprehensions over time and multiply the total by 0.5 and 0.75, assuming, conservatively, that for every 12 people caught, 6 to 8 get in illegally; (2) sum the yearly illegal work apprehensions over time and multiply the total by 0.5 and 0.75 for a similar reason; and (3) multiply the illegal share by the legal stock.

For Latvia, I provide five estimates based on the data I was able to find: (1) multiply the share of informal workers by the number of legal foreign workers, assuming this informal share equals the illegal share; (2) multiply the share of illegal immigrants in the legal immigrant stock to this immigrant stock; (3) multiply the mean yearly inflow of illegal immigrants since Latvia joined the EU by 10 (2004–2013), assuming that prior to EU membership illegal immigrant inflows were negligible; (4) multiply the share of illegal immigrant workers in the legal by the legal worker population stock; and (5) multiply the total number of people apprehended illegally crossing the border over the time period for which there is data by the above 0.5 and 0.75 factors, assuming the reasoning above applies here.

For Brunei, I found data on the number of people deported. Assuming they are all illegal immigrants, I applied the 0.5 and 0.75 factors, for the reason noted above.

For Finland, there are data on the yearly number of caught illegal residents in 2005–2011. An estimate of the number of illegal immigrants residing in Finland uncaptured adds all of these numbers and multiply the total by the 0.5 and 0.7 factors. This number does not account for any illegal immigrants already present in 2005 or any death or departure since that time.

Finally, for the US Virgin Islands, I found data on the number of illegal immigrants captured in the six months from October 1, 2006 to the end of March, 2007. Assuming this period is representative, I get about 6,000 illegal immigrants captured in 2007 through May 2014 (400 x 15 six month periods). I then applied the 0.5 and 0.75 factors.

Concluding Remarks

This paper estimates stocks of illegal immigrants currently residing in the high income world. For the total in the Excel database, on average, the stock of the illegal immigrants residing in the high income world is in the range 22.2–26.9 million. The stock of illegal immigrants itself could be as low as 14.5 million and as high as 42.6 million. These numbers are not small, but are by no means definitive. I treat this database a work in progress and invite others to update or amend it.

NOTE

1 In general, I note that governments provide lower estimates than other source types. This makes intuitive sense as we know most citizens are averse to illegal immigrants and blame leaders for not enforcing border controls, strict surveillance, and deportation. Governments may thus have an incentive to downplay the scope of this immigration.

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