Labor Mobility

Published: May 11, 2013

This is a writeup of a shallow investigation, a brief look at an area that we use to decide how to prioritize further research.

In a nutshell

What is the problem?

Policy barriers in wealthy countries prevent many people who may be able to benefit from migrating from doing so. This is a controversial issue that we have not thoroughly researched, but there are arguments that increasing opportunities for migration could be extremely beneficial to people in low-income countries.

What are possible interventions?

To substantially increase international migration, a philanthropist would likely have to promote policy changes in one or more countries, though some opportunities may exist within existing policy regimes. We do not have a good sense of the likelihood of success of particular attempts to change policy, or what the returns to successful changes might be.

Who else is working on it?

Immigration is a major policy area that receives attention from a variety of research and advocacy groups at the national and international levels. We are not aware of any estimates of how much funding is spent on advocacy related to immigration in the U.S. or other wealthy countries.

1. Why did we look into this area?

  • We have come across research papers by economists suggesting that loosening or removing barriers to labor mobility would have enormous benefits for economic welfare globally (e.g. on the order of a 50% increase in world GDP).1
  • Development scholar Lant Pritchett suggested working to liberalize restrictions on labor mobility as one of three potentially extremely high-return philanthropic activities in an open-ended conversation with GiveWell and Good Ventures staff in June 2012.2

2. What is the problem?

Polls indicate that hundreds of millions of people, particularly in low-income countries, would like to migrate to another country if they were able to.3 Since country of residence accounts for the majority of global variation in income (poor people generally live in poor countries and rich people in rich countries),4 the gains from migration could potentially be quite large.5 Despite the potentially large benefits to migrants, public opinion in wealthy countries is generally strongly opposed to allowing more migrants.6

We have seen three randomized controlled trials studying the impacts of international migration, all of which took place in the context of lotteries held by receiving country governments when visa programs were oversubscribed:

  • Tonga to New Zealand: A program allowing a small number of Tongans to permanently migrate to New Zealand quadrupled household income and tripled household spending amongst migrants four years after migration.7 Results for subjective well-being and mental health are more mixed.8 Migration also appears to decrease per capita consumption one year later for household members who remain at the source, though this may not represent an actual decline because household composition changes.9
  • Samoa to New Zealand: Unlike in Tonga, migration from Samoa appears to increase the income and consumption of household members left behind, but statistical significance of the results varies by specification.10 The study did not collect data on migrants at their destinations, so the impact on migrant wages is unknown. (In both studies of migration to New Zealand, the sample size is fairly limited, with fewer than 200 individuals for key specifications.)11
  • India to the United States: within a single Indian technology firm, winning an H1-B visa and subsequently migrating from India produces a ~$55,000 increase in annual wages at market exchange rates, equivalent to a more than doubling of real wages.12
    These studies are all too small to assess any general equilibrium effects of migration (e.g., whether migration raises or lowers prevailing wages in the sending or receiving locations).13

We have not seen arguments based on global humanitarian values against liberalizing immigration that we consider especially compelling, but we have not conducted a thorough search. Particular areas of concern that we have seen identified but have not fully investigated include:

  • distributional effects on wages at the destination (e.g. driving down wages for less-educated workers)
  • negative impacts of “brain drain,” particularly of medical professionals, on source countries
    potential negative impacts on the subjective well-being of migrants.

Were we to prioritize further research on immigration, we would attempt to more fully address these questions and to seek out other credible humanitarian arguments against liberalizing immigration restrictions.

3. What are possible interventions?

In general, attempting to increase migration would require policy change in wealthy countries, though there are some exceptions where particular existing visa caps are not being met in the U.S.14

We do not have a sense of whether it would be possible, or how much it would cost, to attempt to change a wealthy government’s migration policy. We would expect the costs and returns to vary depending on many factors, including:

  • which country or countries are targeted for policy change
  • what stage(s) of the policy process one attempts to affect
  • the particular migration policy agenda that one promotes.

4. Who else is working on this?

Migration is a major policy area in many developed countries. In the United States, for instance, there are a number of think tanks, policy advocacy organizations, and grassroots groups that are partly or wholly focused on migration. These organizations represent a variety of both pro- and anti-immigration views, though our understanding is that there is relatively little focus on the interests of potential future migrants.

The philanthropic funders that we have come across in our research that appear to have done some work on immigration policy issues are:

  • FWD.us
  • Ford Foundation
  • Carnegie Foundation
  • MacArthur Foundation
  • Atlantic Philanthropies
  • Unbound Philanthropy
  • Rosenberg Foundation
  • Russell Sage Foundation
  • Evelyn and Walter Haas, Jr. Fund
  • California Endowment
  • Krieble Foundation

However, we have not seen any estimates of the total spending on immigration issues by these groups, or by the business interests that we would expect to support some of the same policy goals.

In addition to organizations that work in specific countries, there are also some transnational organizations devoted to the study and support of migration (e.g., the International Organization on Migration).15

5. Questions for further investigation

Our research in this area has been relatively limited, and many important questions remain unanswered by our investigation.

Amongst other topics, our further research on this cause might address:

  • What does the non-experimental economic evidence regarding the impacts of loosening migration restrictions say, and how strong is it? What are the likely humanitarian impacts of increased migration in source and destination countries and how confident can we be?
  • How do the costs and returns to advocacy strategies vary by target country, stage of the policy process, and the particular policy agenda promoted?
  • How much money do immigration proponents and restrictionists spend on advocacy, and how does it vary by country?

6. Sources

Clemens 2011 – Source
Clemens 2012 – Source
Clemens conversation – Source
Gallup 2013 – Source
Gibson, McKenzie, and Stillman 2011 – Source
Gibson, McKenzie, and Stillman 2013 – Source
IOM 2012 – Source (Archive)
Milanovic 2011 – Source
Milanovic 2012 – Source
Mobarak conversation – Source
Pritchett 2006 – Source
Pritchett conversation – Source
Stillman et al. 2012 – Source
IOM homepage – Source

 

SOURCE NAME USED IN FOOTNOTES LINK DATE LINK WAS LAST ACCESSED (FOR EXTERNAL FILES) ARCHIVED LINK (FOR EXTERNAL FILES)
Clemens 2011 Source 5/7/2013 Archive
Clemens 2012 Source 5/7/2013 Archive
Clemens conversation Source – –
Gallup 2013 Source 4/26/2013 Archive
Gibson, McKenzie, and Stillman 2011 Source 5/7/2013 Archive
Gibson, McKenzie, and Stillman 2013 Source 5/7/2013 Archive
IOM 2012 Source 4/26/2013 Archive
Milanovic 2011 Source 5/7/2013 Archive
Milanovic 2012 Source 5/7/2013 Archive
Mobarak conversation Source – –
Pritchett 2006 Source 5/7/2013 Archive
Pritchett conversation Source – –
Stillman et al. 2012 Source 5/7/2013 Archive
IOM homepage Source 6/6/2013 Archive
Expand Footnotes Collapse Footnotes
  • 1.“Even without delving into the details of these studies, the overall pattern is unmistakable and remarkable: The gains from eliminating migration barriers dwarf—by an order of magnitude or two—the gains from eliminating other types of barriers. For the elimination of trade policy barriers and capital flow barriers, the estimated gains amount to less than a few percent of world GDP. For labor mobility barriers, the estimated gains are often in the range of 50–150 percent of world GDP. ” Clemens 2011, Pg 2.
  • 2.“Prof. Pritchett made the following case:The easiest way to increase a poor person’s wealth is to let him or her move to a rich country. Most poor people have low productivity because of the environment that they inhabit rather than because they have intrinsically low productivity. Because of this, they can make much more money if they move to a better economic environment”Pritchett conversation.
  • 3.
    • “However, hundreds of millions of adults would still like to move: Fourteen per cent of the world’s adults – or about 630 million people – would like to migrate to another country if they had the chance, down from 16 per cent, or more than 700 million people, in previous years. These figures are still at least triple the 214 million international migrants the United Nations Department of Economic and Social Affairs estimated worldwide in 2010 – and this 214 million includes children and adults (United Nations, 2009).Where the next wave of potential migrants might come from
      Residents in sub-Saharan Africa remain the most likely worldwide to express a desire to migrate permanently, Gallup finds. Thirty-three per cent of adults across sub-Saharan Africa say they would like to move, although this is down from 38 per cent in earlier readings. Desire also faded slightly in Latin America (from 23% to 20%) and in South-East Asia (from 12% to 9%) between 2007 and 2010.
      In other parts of the world, desire remained unchanged. In the European Union, for example, the percentage of adults who would like to migrate permanently was unmoved at 20 per cent. In Northern America, which includes the United States of America and Canada, the percentage of potential migrants held at 10 per cent.” IOM 2012.
    • Gallop projects that 138 million adults would like to move to the U.S. if they were able: “About 13% of the world’s adults – or about 630 million people – say they would like to leave their country and move somewhere else permanently. For roughly 138 million people, that somewhere else would be the U.S. – the No. 1 desired destination for potential migrants.” Gallup 2013.
  • 4.
    • “If we use the same decomposition between location and class today, when our data are much better than for the past, we find that of the global Gini, which amounts to 65.4 points, 56.2 Gini points or 85 percent is due to differences in mean country incomes, and only 9.2 Gini points (15 percent) to “class”. Not only is the overall inequality between world citizens greater in the early 21st century than it was more than a century and a half ago, but its composition has entirely changed; from being an inequality determined in equal measures by class and location, it has become preponderantly an inequality determined by location only.” Milanovic 2011, pg 7.
    • “Figure 6 plots these two parts, class and location, for the years 1870 and 2000. Around 1870, class explained more than 2/3 of global inequality. And now? The proportions have exactly flipped: more than 2/3 of total inequality is due to location. The implication of this overwhelming importance of location, or which is the same, citizenship (i.e., being a member of a rich or poor country), for our lifetime incomes can be also very well captured by another exercise. We divide the population of each country into 100 income percentiles, ranked from the lowest to the richest. Now, if we run a regression with income levels of these percentiles (for 120 countries, this gives 12,000 observations) as the dependent variable, and on the other side of the regression, use as the only explanatory variable the mean income of the country where each percentile comes from, we explain between more than one-half of variability in individual incomes. This is a remarkable achievement for a single explanatory variable. Differently put, more than fifty percent of one’s income depends on the average income of the country where a person lives or was born (the two things being, for 97% of world population, the same). This gives the importance of the location element today. There are of course other factors that matter for one’s income, from gender and parental education which are, from an individual point of view externally given circumstances, to factors like own education, effort and luck that are not. They all influence our income level. But the remarkable thing is that a very large chunk of our income will be determined by only one variable, citizenship, that we, generally, acquire at birth. It is almost the same as saying, that if I know nothing about any given individual in the world, I can, with a reasonably good confidence, predict her income just from the knowledge of her citizenship.” Milanovic 2012, pgs 19-20.
  • 5.“Even without delving into the details of these studies, the overall pattern is unmistakable and remarkable: The gains from eliminating migration barriers dwarf—by an order of magnitude or two—the gains from eliminating other types of barriers. For the elimination of trade policy barriers and capital flow barriers, the estimated gains amount to less than a few percent of world GDP. For labor mobility barriers, the estimated gains are often in the range of 50–150 percent of world GDP. ” Clemens 2011, Pg 2.
  • 6.“In Western Europe, proposals to increase levels of immigration were dramatically unpopular. The proportion of the population that favored reducing immigration was more than three-quarters in Germany and Italy, and more than 60 percent in the United Kingdom, the Netherlands, Sweden, and Norway. Moreover, nearly all those who do not want migration reduced want it to remain the same. In no country in receiving Western Europe was the support for any increase in immigration (either “a little” or “a lot”) higher than 10 percent. In Japan, a country where migration had been quite low, almost 16 percent of the population favored some increase in immigration—but even there, almost three times as many wanted immigration reduced.
    In the United States and New Zealand, countries that were populated primarily by migration, opposition to increases in migration was also wide- spread. Of course, this is the context of the fact that actual immigration was increasing, a point we return to below. Of all the industrial countries, Canada emerges as the most favorably disposed to increased immigration. This means that in Canada one in five people favored increasing migration and only 42 percent favored reducing migration. So, at least in this particular survey as of 1995, in the industrial country that was the most “migrant friendly,” “only” twice as many people wanted to reduce the level of migration as wanted it increased.
    It is not as if those in favor of reducing migration are counterbalanced by a large group that opposes restrictions on immigration and wants increased mobility. In nearly every instance, those who want reductions in migration outnumber those who want it by ten to one. The World Values Survey reports that only a tiny fraction of the population (between 4 and 14 percent) agreed with the statement that their country should “let anyone come” (see table 3-5 below).
    Not surprisingly, the views of governments reflect the views of the voters. In the UN International Migration Report 2002 (UN Department of Economic and Social Affairs 2002), the policy stances of governments were reviewed. Of forty-eight “more developed” country governments, only two thought the level of immigration was “too low,” while fourteen thought it was “too high” and thirty-two satisfactory. Of these same forty-eight “more developed” countries, twenty-one reported undertaking policies to lower immigration while again only two had policies to raise the level of immigration.” Pritchett 2006, pgs 73-75.
  • 7.
    • “The household income of migrants doubled within the first year of moving to New Zealand. The impact on per capita household income was lower, at about 60 percent, because employment rates initially fell for the secondary migrants accompanying the principal applicant. Moreover, many of the migrants initially moved in with extended family members while they were establishing in New Zealand so household size relative to the number of income-earning members rose compared with in Tonga. But, by the time of the wave 2 survey, all of the migrants had transitioned into their own accommodation, with average household size lower than in Tonga because the eligibility restrictions prevented extended family co-residents from migrating with the Principal Applicant. Consequently, in wave 2, the per capita estimates of impacts exceed the household-level estimates. Even for the results with control variables and restricting attention to the balanced panel, the wave 2 income effects are very large; total household income had risen by 297 percent due to migration while per capita income was 340 percent higher.
      The final results in Table 2 are for total expenditures and the food share of expenditures, both of which are used as indicators of permanent income effects. The estimated impacts of migration on household and per capita expenditure are smaller in magnitude than the impacts on income, as would be predicted by the permanent income hypothesis, but are still extremely large in magnitude with a 214-231% increase in household expenditure and a 237-259% increase in household expenditure per capita. Similarly, the fall in the food share of total expenditures, by over 47 percentage points, indicates a large positive improvement in real incomes for the migrant households.” Stillman et al. 2012, pgs 18-19.
    • “The first wave of the survey in New Zealand in 2005 covered a random sample of 101 of the 302 Tongan households that migrated as successful participants in the 2002-05 PAC ballots. The second wave was fielded in 2008 and re-interviewed 89 of these households. Of the remaining households, ten had either re-migrated to a third destination country or moved to outer areas of New Zealand where it was too expensive to travel for fieldwork, while there was one refusal and one non-contact. At the time of the first wave of the survey, migrants had spent an average of 11 months in New Zealand. The second wave was fielded approximately 33 months later.” Stillman et al. 2012, pgs 11-12.
  • 8.“Table 3 reports the impact of migration on the happiness of migrant principal applicants, on the other components of their MHI-5 and on the welfare and respect ladders and income adequacy. The results in the first column show the short-term effects of migration are to leave happiness unchanged. However, the other components of mental health rise significantly, with an average treatment effect of about 1.8 points; equivalent to about one standard deviation. This divergence between components of mental health suggests that a focus just on happiness may miss some broader improvements in psychological well-being brought about by migration.
    The results from wave 2 (in columns 3 and 4) show that the divergence in impacts on happiness versus other mental health components increases over time. The happiness scores of migrants are approximately 0.8 points lower than they would have been in Tonga, about four years after migrating. This finding might be taken as evidence for claims in the literature that migration may make immigrants less happy than if they had stayed put (Bartram, 2010). But that interpretation is weakened by the very substantial rise in the other components of mental health, of about three points, which is equivalent to one quarter of the wave 2 scores for the control group in Tonga. Putting happiness back in with the other mental health components, the overall MHI-5 score of migrants in wave 2 is at least two points higher than it would have been if they had stayed in Tonga; this significant improvement in mental health shows that the short-term gains noted by Stillman et al., (2009) are not just a transitory effect of migration.
    The results for the remaining subjective well-being indicators that are measured by the survey – the welfare ladder, the respect ladder and income adequacy – also show a diversity of impacts of migration. There is no impact of migration on the migrants’ position on the welfare ladder, but they go down about 0.9 steps on the respect ladder (equivalent to a drop of about one-eighth of the mean score for the control group in Tonga). Conversely, self- rated income adequacy goes up by at least 0.2 points with migration, which is equivalent to about one-tenth of the mean score for the control group. None of these patterns or magnitudes changes if the control variables are used or if the sample is restricted to the balanced panel of principal applicants. Thus, in contrast to the consistently large and positive impacts of migration on objective well-being, there are more subtle and complex effects on subjective well-being with some indicators improving, others static, and happiness and respect falling.” Stillman et al. 2012, pgs 19-20.
  • 9.
    • “Since households in Tonga that have had some members move to New Zealand under the PAC have fewer members, we examine the impact on per capita incomes and alternatively on adult equivalent incomes.18 The results in table 5 for log total income indicate that the families of migrants have 25% to 26% lower incomes than the families of non- migrants, when no control variables are included, regardless of whether income is per capita or per adult equivalent. The estimated impact is a 22% to 24% decline in income when control variables are added, but the per capita estimate is no longer statistically significant. If we instead estimate a linear model, which is more sensitive to outliers, we find that income declines by $1,000 per capita or $1,250 per adult equivalent (19% to 20% of the mean for treatment group households) for families of migrants when there are no controls and by $641 per capita or $927 per adult equivalent (12% to 14%) when controls are included. In neither case are the estimates significantly different from 0.” Gibson, McKenzie, and Stillman 2011, pg 1307.
    • “We have seen that migration reduced the per capita resources available in migration households. However, since we do not know how resources were distributed within the household prior to migration, it is difficult to know whether these changes reflect a genuine change in resources available to the family members left behind, particularly as we have shown that the adult movers contributed significantly more to the household in terms of labor earnings than do the adult stayers.
      Nevertheless, we believe that the available evidence does suggest that resources are pooled within Tongan households in the absence of migration. First, prior anthropological investigations argue that food and other resources are shared equally among extended family members within a household (Pollock, 1992). Second, we use the stayer ballot-loser households to test whether there is an equal relationship between the age and gender composition and earnings of stayers and movers in the household and household diet and cannot reject the null hypothesis of equal effects across the two groups for any of the food groups at the 5% significance level.23 The HIES shows that food consumption is approximately two-thirds of the household budget, so income-pooling effects on diet seem likely to extend to total consumption. Third, if resources were unequally shared within the household, we should expect to see differences in food intake manifest themselves in differences in anthropometric measures between stayers and movers. However, when we regress anthropometrics on household fixed effects and a dummy for being a stayer, we find no difference in child height for age or BMI for age, or in adult BMI between stayers and movers.24 This evidence leads us to believe that the fall in household resources per capita from migration does indeed represent a genuine fall in resources available to the stayers.” Gibson, McKenzie, and Stillman 2011, pg 1310-11.
  • 10.
    Gibson, McKenzie, and Stillman 2013:

    • “The point estimates suggest that households which sent emigrants now have larger total household income and consumption than households who were unsuccessful in the lottery, but large standard errors on these estimates make the estimates statistically insignificant. The results do show a change in the composition of household income. Income from agricultural production and income from remittances are significantly higher, by 245% and 75%, respectively, relative to unsuccessful households, while household labor earnings are lower (but not significantly so).”
    • “Table 5 examines the impact of emigration on per person resources. We now weight the estimates by household size and hence the results indicate the change in per person resources for the average individual. These results show that left-behind household members are better off in comparison to members of households with lottery losers. Average consumption is approximately 17% higher in per adult-equivalent terms and income is approximately 23% higher (although neither is statistically significant).11 Since the changes in income and consumption are similar, this suggests that these changes associated with emigration and remittances are being viewed as shocks to permanent income by the left-behind household members. There is some weak evidence that these gains become smaller over time, both because household size is rising and because the income gains are declining. However, these results are also consistent with the impacts being independent of how long the emigrants have been gone.” pg 269.
    • “Finally, table 6 examines the impact of emigration on poverty. Again, we weight the estimates by household size and hence the results indicate the change in poverty for the average individual. The basic needs poverty rate among individuals living in households that sent Samoan Quota emigrants is 23 percentage points lower than for households with lottery losers. Since the poverty rate among individuals in unsuccessful households is 37%, this represents a 62% reduction in head count poverty. However, there is no measured effect of emigration on the food poverty rate that captures deeper poverty (with only 12% of the lottery loser households below this line), nor is there any effect on the poverty gap ratio at either poverty line.12 This indicates that the main impact of having family members migrate to New Zealand was to lift individuals who were just below the basic needs poverty line out of poverty, with insignificant effects on the much smaller proportion of individuals who were poorer than this. The impact on the subjective poverty reported by an individual adult respondent in each household is negative but also statistically insignificant. Again, there is some weak evidence that any possible poverty reduction declines over time, but the years since migration term is neither significant nor the same sign across different poverty measures.” pgs 269-270.
    • “We find that migration reduced basic needs poverty among former household members. This contrasts with the short-term impact of migration for Tongans moving to New Zealand through a similar lottery program—in McKenzie et al. (2007) we find an increase in poverty for those left behind. Comparing the results, the difference stems from a much larger fall in house- hold labor earnings in Tonga than in Samoa, and a fall in agricultural production in Tonga compared to a rise in agricultural income in Samoa. The increase in remittances is similar in both cases.
      In Tonga, we found that the movers earned twice the weekly income as the stayers within a potential migrant household (Gibson et al. 2011), which was why household earnings declined so drastically when these individuals migrated. In contrast, fortnightly earnings for stayer 18–45-year-old adults in Samoa average 179 Tala, versus 211 Tala for the movers (p = .32).14 Thus, Samoan households rely relatively less on the labor earnings of the potential migrants before migration and so suffer less opportunity cost of their absence in terms of these forgone labor earnings. It is also possible that the much longer history of migration through the SQ has given households more time to learn how to adjust to the absence of members, potentially through getting them to set up a lot of agricultural production beforehand. These differences highlight the importance of context in understanding the impacts of migration and of replicating these experimental studies in more locations where possible.” pgs 275-6.
  • 11.See Table 4 (Pg 267), Table 5 (Pg 269), and Table 6 (Pg 270) in Gibson, McKenzie, and Stillman 2013 and Table 5 (Pg 1308), Table 6 (Pg 1309), Table 7 (Pg 1310), Table 8 (Pg 1311) in Gibson, McKenzie, and Stillman 2011.
  • 12.
    “The effect of location outside India on 2009 earnings is US$54,949 after one year and US$58,203 after two years, roughly a sixfold increase in earnings, measured at market ex- change rates. Measured in PPP dollars, the same treatment effects are PPP$38,958 after one year, and PPP$38,674 after two years, representing an increase in real wages by a factor of between 2 and 2.5. The accompanying standard errors show that all of these estimates are statistically precise well below the 5% level.
    The table also juxtaposes these estimates with the simple differences in earnings for comparable software workers between the U.S. and India reported by Commander et al. (2008). The effect of location outside India on exchange-rate earnings is over three quarters of the simple difference in earnings. This suggests that a large majority of the unconditional difference in earnings is due to the place that those workers are located, and not to any other observable or unobservable difference between those workers.” Clemens 2012, pg 15.
  • 13.This issue was discussed in a conversation GiveWell had with Professor Mushfiq Mobarak. Mobarak conversation.
  • 14.
    • “The United States offers two types of visas for seasonal low-skilled workers. One is the H-2A visa, which is designed for agricultural workers, and the other is the H-2B visa, which is designed for nonagricultural workers—mostly hotel and resort workers. There is no quota on the number of H-2A visas that can be granted, and the quota on the number of H-2B visas is 66,000 per year. Over the past few years, the quota for H-2Bvisas has not been met.” Clemens conversation.
    • It is less obvious that these gaps represent a problem: if more people could come if businesses wanted to employ them but businesses don’t seek them out, then there may simply not be very many profitable employment opportunities that could be covered by the relevant visa program. That said, it may also be the case that bureaucratic constraints limit the profitability of potentially employing migrants, leading to under-utilization of the available visas, leaving open the possibility for a valuable philanthropic option:“The number of migrants who get H-2 visas is much smaller than it could in principle be. A major reason for this is that there are very substantial bureaucratic hurdles that employers must clear in order to hire migrant workers. The North Carolina Growers Association is the largest user of the H-2A visa program. It brings roughly 15% of the total workers who obtain the visas. The association has many complaints about the program. For farmers in North Carolina to hire migrant workers, they’re required to:
      • Post advertisements in American newspapers and at state unemployment agencies for two months.
      • Hire any American applicants (except for those who are physically
        incapable of doing the work), even well after the growing season begins and they have already filled the positions with any foreign workers.
      • Fill out a great deal of paperwork and pay fees.

      The process has to be completed for every single worker hired (even if the employer is hiring migrant workers at scale) and every year (even if the employer has been hiring migrant workers for a long time). The farmers who hire migrant workers are effectively required to pick the number of workers who they want to hire several months before they’re able to assess how many they need based on weather conditions.
      Because of the bureaucratic hurdles, people on H-2 visas represent less than 5% of manual seasonal labor done by non-U.S. citizens, and most manual seasonal laborers are unauthorized immigrants.” Clemens conversation

  • 15.IOM homepage