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Weekly OBAG roundup 07 2014

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This is part of a series of weekly posts with the most interesting content from the Open Borders Action Group on Facebook. Do join the group to weigh in on existing discussions or start your own (you might want to read this post before joining).

Thought-provoking general questions or general observations

Discussions of specific historical or current situations

Hypotheticals

Outreach and meta

What will the rapid economic growth under open borders look like?

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Open borders will lead to rapid economic growth in some countries, particularly the countries that receive migrants. This will be true even if the per capita income of natives doesn’t rise much (or even if it falls). The total size of the economy will grow. The situation with countries sending migrants is more complicated: the decline in population means that the size of the economy could shrink, even if per capita income rises. On the other hand, very high remittances or reverse migration and joint multinational businesses could offset the huge population loss. This blog post explores the sorts of things that could happen under open borders.

A few historical and current examples worth considering:

  • The United States in the second half of the 19th century: The example fits well in the following ways: immigrants were quite poor, the economy as a whole was backward but improving fast, and the immigrants were from many different cultures and spoke many different languages. The example fits badly in the following ways: the US was at the technological frontier, the place premium wasn’t huge (both sending and receiving countries were poor), and the whole event occurred in a time when many other aspects of global culture and technology were different. In particular, due to greater costs of transport and communication, and many other reasons, the total foreign-born proportion of the population was not too high: it peaked at 15% in 1910, compared to about 13% now under fairly closed borders in the US (more here).
  • China from after the death of Mao Zedong in 1976 (we expect to write more about China later; for now, check out our blog posts tagged China): The very rapid “catch-up” economic growth in China is comparable to the sort of growth we’d expect to see in migrant-receiving countries under open borders. The scale of rural-urban migration over the preceding and coming decades is in the hundreds of millions, comparable to the levels we’d expect with a decade or more of open borders. The proliferation of cities in China in recent years provides a model for what might happen under open borders. On the flip side, migration in China is happening across a far more homogenous linguistic and cultural milieu than what we’d expect under open borders. Moreover, China has a single government that can (and to some extent does) coercively restrict and coordinate migration in ways that wouldn’t work for global open borders unless there is world government or some supranational body that exerts heavy control over the coordination of international migration. China is also unrepresentative of global open borders because the place premium isn’t that huge.
  • India since its economic liberalization beginning in the late 1980s and with the main big step around 1991 (more on India here; see also all blog posts tagged India): India offers an example that’s both better and worse than China in terms of predicting what will happen under open borders. On the “better” side, there’s the fact that India is linguistically more diverse, so that many of the global challenges faced by migrants are experienced on a smaller scale in India. Although India is also religiously diverse, the religious diversity isn’t too strongly linked to location (the major religions are dispersed over many locations). India also offers a better model of a situation where the government does not plan either to stop migration or to prepare to accommodate it, unlike China, where both national and local governments have taken a more proactive approach to regulating flows. As of 2001, India measured 191 million internal long-distance migrants, about 20% of the population then. This number is comparable with the sort of migration magnitude we’d see under open borders, though it’s somewhat less than the amount of rural-urban migration in China. As with China, the place premium isn’t big enough to test some of the concerns associated with open borders. On the “worse” side, India is an even poorer country than China, so the parts of India that receive immigrants serve as bad models of how the destination countries under open borders would look.
  • The European Union today (see this related post by Hansjoerg and all our posts tagged the EU): This example is better suited in the respect that the target countries of migration are wealthy First World countries, which we expect will see a lot of immigration under open borders. But none of the source countries is too poor: the poorest countries in the EU are Romania and Bulgaria, which are middle-income countries (things will become more interesting once Albania joins). Quantitatively, migration between EU states on the whole is much lower than intranational migration in India and China, and much lower than what we’d predict under global open borders. About 3.2% of EU residents were born in another EU country, compared to 6.3% who were born outside the EU (see here and here).

The following table provides a comparative summary of the four cases considered above in terms of how good they are in their similarity to how we expect open borders to unfold (so “good” here means “good as a model for figuring out how things will be under open borders”, not “normatively good” or “desirable”):

Attribute 19th century US China India EU
Scale of migration Moderate Good Good Bad
Absolute poverty in source countries Good Good Good Bad
Absolute wealth in target countries Moderate Moderate Bad Good
Place premium Moderate Moderate Moderate Moderate
Cultural heterogeneity Moderate Bad Moderate Moderate

A few other examples that aren’t quite as good because the scale involved is too small, but are still interesting in some respects:

  • Open borders between Puerto Rico and the United States (see this blog post by Bryan Caplan): The place premium was moderate, the cultures were different (English versus Spanish). The scale of migration, over the long term, was huge relative to the sending country, but small relative to the receiving country. This example isn’t so helpful for our purpose because the US is too huge relative to the Puerto Rico for the migration to have had huge effect; however, some parts of the US (such as New York and Florida) have been influenced by Puerto Rican migration.
  • Israel has had open borders of sorts for Jews from around the world. A large number of East European and Russian Jews have migrated to Israel. Joel Newman crunched the numbers in this blog post. Although this is open borders of sorts, the small absolute size of the experiment makes it uninteresting in terms of figuring out how migration works at scale and can lead to rapid economic growth.
  • South Africa’s end of internal apartheid (discussed by Grieve Chelwa here) is also interesting, but again the scale of migration is insufficient to provide a clear sense of how things will proceed under open borders. The South Africa example is more interesting in that it involves a significant policy change in the open borders direction, but the focus of this blog post is more on the economic growth facilitated by mass migration than on the suddenness of the change.

The mix of labor and capital

Economic growth has been classified as intensive growth and extensive growth. Intensive growth involves changes in the mix of inputs and/or changes in the production technologies, i.e., the introduction of new ideas or new methods to produce more from the same inputs. Extensive growth involves an increase in inputs.

Now, to some extent, the change under open borders is extensive: a lot more labor is being added to the world economy. But in another respect, the change is intensive: the ratio of labor to capital shifts drastically worlwide, and even more so in countries that are migrant destinations. For more on this point, see Nathan Smith’s blog post on John Kennan’s paper on open borders. I quote a part of Kennan’s original paper that Nathan quoted; Nathan’s elaboration is worth reading at the link:

These gains are associated with a relatively small reduction in the real wage in developed countries, and even this effect disappears as the capital-labor ratio adjusts over time; indeed if immigration restrictions are relaxed gradually, allowing time for investment in physical capital to keep pace, there is no implied reduction in real wages.

I see two sorts of trajectories that could unfold:

  • The planned trajectory is one where borders are opened gradually and labor regulations are modified to better use the new labor mix. In this case, people have more time to accumulate more capital stock. I would expect that in this case, industry will play a big role in migrant-receiving countries: entrepreneurs and industrialists will set up large factories in anticipation of the huge migrant workforce they can have access to. They will undertake huge construction projects or expand agribusinesses.
  • The unplanned trajectory, where migration barriers are removed quickly with little coordination and planning, would probably see more of a shift to the services sector, which is less capital-intensive and where new people can join quickly.

Indeed, of the examples of China and India, the more planned and controlled case (China) has had more reliance on industry whereas the more chaotic case (India) has had more reliance on services (see more here). Note that in the longer run, I’d expect everything to move in the direction of services, when industry becomes so efficient that adding more people isn’t worthwhile at all (even at zero wages). But we’re far from there yet.

What about growth due to technological progress at the frontier? It’s possible that the progress of the frontier will not be affected much by open borders, but I personally expect that frontier progress will happen somewhat faster under open borders than under the counterfactual. This is the basis of the innovation case and the one world vision of open borders. I do expect that sending countries are likely to experience intensive growth and technological progress due to the circulation of people and ideas, though whether their economies as a whole grow or shrink would depend on how the magnitude of this effect compares with the decline in population. For arguments that open borders impede the progress of the technological frontier, see our page on killing the goose that lays the golden eggs.

The creation of new cities

There’s evidence to suggest that migrants who travel long distances tend to move to cities, for a variety of reasons. While living in one’s own village or small town may be preferable for many, living in a small town that one does not have connections with is hard. Cities are more conducive to strangers from faraway lands. They offer a wider range of job opportunities as well as amenities. The existence of a larger population allows for restaurants and supermarket products offering ethnic cuisine that wouldn’t be economically feasible in a smaller town.

It’s likely that there will be a lot of migration to the existing top cities of the world, but these cities have sky-high rents and are unaffordable to many poor migrants who don’t have enough skills to find jobs that could pay those rents. What I expect to see is many new cities crop up. Most likely, these cities will grow from existing small towns, potentially disrupting the lifestyles of residents of those towns. Natives are likely to have a mixed reaction: those who wanted city life but didn’t have the money for the big cities can benefit from the greater urbanization of their small town, and those who didn’t like city life may experience a decline in their quality of life (some of them may migrate to other places in their own country to get away from the overcrowding). Recall also Nathan Smith’s land value windfall argument: the price of new housing of a given quality can remain the same or even decline, even as the price of existing housing can keep rising due to an increase in the demand for living in established cities and towns.

It’s also possible that entire new cities can be created from scratch. One can imagine, for instance, a few companies setting up large factories in an area, and a huge amount of cheap housing for the people working in those factories. Another possibility is that new cities will emerge in wasteland that is at the periphery of existing cities, or from suburban or exurban regions of existing cities.

A useful historical model is China, which is undergoing the world’s most rapid and large-scale urbanization. For more, see Wikipedia, the McKinsey Global Institute report, and this presentation for a Stanford University course. In 1976, about 18% of China’s population was urban, and now about 52% is. It is estimated that by 2025, China will add over 350 million more people to its urban population, of which 240 million will be migrants. That 240 million is more than the number of people who indicate the US as their first-choice migration destination. The following are some key features of growth in China:

  • The rate of migration itself has been accelerating and may be plateauing now, though it will eventually start decreasing once rural areas have depopulated. While part of the mechanism here is diaspora dynamics, the more likely explanation is simply the increasing rate at which the economy is restructuring to increase demand for labor in urban areas and decrease it in rural areas.
  • The creation of new cities is concentrated in the middle phase (city creation was most intense around 1990-2005) rather than very early (when migration is still just beginning, existing cities have enough room for the initial migrants, and it’s not clear where more people will want to settle) or very late (when the patterns of migration are already set).
  • New cities are generally created close to existing cities.

Increase in international trade and foreign direct investment

Immigration and trade can be both complements and substitutes, but I expect that, unless tariffs are raised havily, more migration will facilitate more trade. Multinational small businesses run by family members around the world will become more common. Larger businesses will find it easier to set up shop in a greater range of countries. Diaspora will be eager to invest or get their associates in their new countries to invest in ventures in their source countries, so there will be more foreign direct investment. As people become better connected, there will be a reduction in the anti-foreign bias that motivates restrictions on trade and FDI. Another relevant point is that the move towards open borders is likely to be accompanied by a move towards free trade and FDI, because both proceed through the gradual expansion of free trade and free migration zones (such as the European Union).

A somewhat different vision

I’ll quote below Nathan’s detailed questionnaire answer (this is answer #4 in this very long blog post):

Some of the major problems of developed countries today would be solved by open borders. Government debt becomes less burdensome when population and total GDP rise, even if per capita GDP falls. As mentioned above, long-term demographic problems of shrinking and greying populations would be mitigated or eliminated by open borders (this does depend on the composition of immigrants, but given the relative youthfulness of the world population as a whole and the greater propensity of the young to move, the prediction that open borders would help can be made fairly confidently). Almost all homeowners and owners of real estate would enjoy a windfall benefit from rising population as demand and prices rise. This effect would not be offset by losses to renters, or to people unwilling to sell, from higher rents and property taxes. As cities expanded, renters could still live in comparably dense, interesting places, and homeowners who stayed put would get the windfall not in cash but in being through the midst of more economic activity (i.e., more shops, restaurants, entertainment, interesting streets, jobs and business opportunities, etc.– all the amenities of urban living for which people pay high urban rents).

Savers and owners of capital would tend to benefit as well, from an abundance of investment opportunities, but there would be downward pressure on wages. Crudely speaking, “unskilled” workers would see their wages fall, while some “skilled” workers would probably see their wages rise. But then, some of the basic skills Americans take for granted, like speaking native English, cultural fluency, and driving cars, would become “skills” for which premia could be earned. Immigrants would help poorer natives as customers, by creating a mass market for low-price goods, and giving companies a stronger incentive to pursue “frugal innovation.” There might be more business opportunities for entrepreneurially inclined natives even without a lot of education. Overall, it is extremely likely that natives as a whole would benefit, but without deliberate efforts to prevent it via fiscal policy, a substantial minority of natives would be likely to see their living standards fall due to open borders.

I would both advocate and anticipate that policy would do much to protect the least fortunate natives against a fall in living standards due to open borders. Moreover, this would be fiscally feasible, because open borders would greatly expand the tax base. Some natives might find jobs scarce and/or wages very low, yet receive transfer payments from the government which would enable them to live a “middle class,” house-and-car-in-the-suburbs, lifestyle. Others would see their wages fall but find themselves more than compensated by a rise in the price of their home and the value of their stockmarket portfolio– while also, perhaps, enjoying new transfers and/or tax cuts from a government flush with revenues from immigrant taxes. The hardest part of adjustment would be the moral impact of labor falling in value. One tenet of what I call “the macroeconomic social contract”– that anyone who is willing to work should be able to find a job that enables them to earn a decent living standard– would be further undermined.

Also discombobulating for natives would be the emergence of vibrant shantytowns and ethnic districts on an enormous scale. Pre-assimilation would mitigate the problem of absorbing immigrants into mainstream society, though on the other hand the number of immigrants would be larger than in the 19th century both in absolute numbers and as a share of the population. But Americans would hear more languages spoken on the streets, see more holidays celebrated, see a wider variety of religious buildings and of clothing. There would be neighborhoods where native-born US citizens would have the experience, charming to some but frightening to others, of being on American soil yet feeling like they were abroad. European countries, I expect, would face a different problem, namely, that some immigrants would prefer to assimilate to an “Anglobalized” international bourgeoisie, rather than to Dutchness or Norwegianness or Italianness. They would have to cope with large populations of foreigners who seemed content to reside permanently in their countries, getting by with English. Sweden or the Netherlands might see their living standards rise under open borders, even as Swedish and Dutch faced displacement by English as the nation’s first language. (That might happen anyway, but open borders would accelerate it.)

While the native-born citizens of the rich world need not see their living standards fall and most to all would probably see them rise, likely by a lot, under open borders, there would be far more poor people in the rich world. Germans and Danes and Italians and Washingtonians and Californians would have to get used to seeing a lot more deep poverty on the streets, and content themselves with knowing that there was much less poverty in the world because there was a little more at home. The moral underpinnings of the national socialist models of society that prevailed in the 20th century would have to be abandoned. Territorialism as a meta-ethical prejudice would have to be refuted at the level of reason and then wrung out of people’s intuitions.

Selection effects for migrants: some a priori possibilities

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This post combines many different threads I’ve explored in earlier posts. Back in July 2013, I wrote a post arguing that it’s important to get a handle on both the quantity and the selectivity of migration. Recently, I wrote a series of blog posts laying out a detailed conceptual framework for the empirical analysis of migration (introductory post here, describes and links to other posts). While laying out this conceptual framework, I noted that, under any policy regime other than complete closed borders, there is likely to be both a selection effect and a treatment effect for migrants. Specifically, in part 3, I considered a situation where we assume for simplicity that the people who do not migrate are not affected by the act of migration. In that case, we can concentrate on selection and treatment effects for migrants and ignore the treatment effects on non-migrants. Our goal was to discuss the rank-ordering and quantitative comparison of the following four values (where X is the indicator of interest):

  1. Performance of natives of target country B on indicator X.
  2. Performance of natives of source country A (who would not move under either policy) on indicator X.
  3. Performance of potential migrants on indicator X if they were allowed to migrate (i.e., in the migration scenario).
  4. Performance of potential migrants on indicator X if they were not allowed to migrate (i.e., in the no-migration scenario).
  5. Ability to plan and execute a move.

Note that:

  • The difference between (2) and (4) measures the selectivity of migration relative to the source country.
  • The difference between (1) and (3) measures the selectivity of migrants relative to the target country, or equivalently, to their failure of assimilation (the assimilation may be “upward” or “downward” depending on how the migrants compare with the target country natives).
  • The difference between (3) and (4) refers to the treatment effect of migration on migrants.

The goal of this blog post is to come up with a priori arguments on how migrants might be selected on various parameters. We’re not concentrating on the treatment effect directly, except insofar as beliefs about the treatment effect affect the selection of migrants. In some cases, we cite empirical evidence to support the claim. But the goal is not to make concrete empirical predictions, but to lay out general considerations that would help make concrete predictions for specific migration policy regimes.

Because of the vagueness of our analysis, we don’t distinguish heavily between selectivity of migrants relative to source countries and selectivity relative to target countries. However, our arguments, as stated here, apply a priori far more to selection relative to source countries than to selection relative to target countries. This follows from the nature of the analysis: we’re trying to figure out who, from a given bunch of people in the same environment, would end up moving. Therefore, these are best thought of as arguments about emigrant selectivity (comparing (2) and (4)) than about immigrant selectivity (comparing (1) and (3)). At the end of the blog post, we’ll discuss what we can infer about immigrant selectivity from the information.

Also, for the most part, I restrict attention here to considerations that would be relevant even under open borders. There are some forms of selectivity that arise from fiat: migration policy dictates that migrants must satisfy a set of conditions in order to be allowed in. We discuss these only in passing here, and will return to explicit policy selection in a separate post (more remarks on this at the end of this post). Note that I ignore explicit policies in the post but I certainly consider them quite important. I am not an economic determinist.

Costs of moving

Migrants are moving to a new place. Even under an open borders regime, moving requires nontrivial fixed costs in terms of time, money, and emotional energy. The magnitude of the costs depends on the geographic distance moved, the cost differential (moving to a place with a higher cost of living means one’s savings are less use for covering the initial costs of setup, even if one expects to eventually recoup those costs through higher earnings), as well as the cultural and linguistic distance between the source and destination. Note that all these apply even under open borders. In a regime with migration restrictions, there are additional costs of time, money, and uncertainty in applying for permission to move. Depending on the feasibility of return migration, one may also need to dispose off assets before making the move. Those crossing borders illegally need to incur coyote fees and undertake time-consuming and dangerous journeys to reach their destination.

What attributes does the high cost of moving select for? It’s hard to say, but here are some guesses:

  • Money: People who have more money can afford the costs of moving more easily.
  • Strong future orientation (i.e., lower discount rate): People who think of life a few years ahead are more likely to be willing to migrate than people who engage in hyperbolic discounting.
  • Willingness to break ties: People who are heavily attached to their family and home culture would find the move more difficult, whereas people who define themselves less by their present relationships can move more easily.
  • Adventurousness, openness to experience, and willingness to take risks

Opportunity costs of migration

When people migrate, they leave behind their home, family connections, and a culture that they are more familiar with and may be attached to. What sort of people are willing to leave that behind? Here are some guesses:

  • People who have little to lose by leaving are most likely to do so. This could be because they are at high risk of being victimized by violence, are heavily discriminated against by people where they live, are cultural misfits, or cannot find any use of their job skills where they currently live.
  • People who have skills or assets that cannot be transported easily and can be leveraged most in the homeland are least likely to leave. For instance, people who are good-looking by the standards of their culture may have the best prospects in their homeland (however, if a huge diaspora from the country already exists, they might be able to marry a member of the diaspora settled elsewhere through a family connection or other introduction). People who inherit a big family business that they can continue running, but aren’t particularly entrepreneurial, may just prefer to stay where they are to keep running the business. People with skills in politics have the best shot at politics in their home country, given that voters everywhere are likely to discriminate in favor of people who were born in the country and fit in culturally and linguistically. People who have completed expensive location-specific qualifications (such as in law) may prefer to stay in the home country because they’d need to re-qualify to practice law in a new country.

Note that there’s a contradiction of sorts between the little to lose criterion (which suggests that poor people may be more keen to migrate) and the observation that wealthier people can more easily afford to migrate. We’ll talk more about this later.

Benefits of migration

Migration generates huge benefits for some people, and scant benefits for others. The main benefit of migration from lower-productivity regions to higher-productivity regions is the place premium: one can earn more with the same skills simply by migrating to a new country.

The following attributes predict the benefits of migration:

  • Larger absolute wage gains predict migration. Highly skilled individuals, who command high incomes in general, are likely to have large absolute wage gains.
  • Larger proportional wage gains predict migration. Increasing one’s income from $1000/year to $10,000/year looks a lot more attractive than increasing one’s income from $30,000/year to $40,000/year.
  • Greater knowledge of, affinity for, or ability to learn, the language, customs, and culture of the new place predicts more migration.
  • Greater ideological or political affinity with the place they’re moving to (see Ilya Somin’s blog post on the subject).
  • Presence of diasporas from the source country in the target country can make migration more attractive. This is part of the diaspora dynamics model developed by Paul Collier.
  • Other geographical and health-related considerations could play a role. For instance, I’ve been told that in the 19th/20th century US there was a wave of migrants with lung diseases to the southwest to benefit from the dry air there. This was intranational migration, but presumably there could be international migration for similar reasons under open borders. The selection effects here are unclear, for instance, it may be that emigration of the unhealthy makes it such that the people who stay on in inhospitable climates are unusually healthy and fit.

Migration for one’s children

In my blog post on whether there might be too much or too little migration, I talked about how the costs of migration are borne by the migrant, but the benefits are shared by the descendants. I had noted at the time that, because migrants may not fully take into account the benefits to their descendants (even though they care somewhat about their descendants) this might lead to too little migration.

I want to bring up the same point, but with a focus on selectivity rather than raw quantity. People who strongly care for the future of their children and later descendants (including unborn descendants) are more likely to be willing to migrate. This probably selects for two things:

  • Strong future orientation (we already talked about this in the context of overcoming the costs of migration, but it takes on added importance if one is thinking of one’s children or grandchildren, particularly the unborn ones).
  • Greater love or concern for one’s future family. Note that this is in some tension with the fact that migrants are generally more willing to break ties with their existing families in order to migrate.

I’m planning to do a post on how migration can be considered a sacrifice for future generations, where I’ll explore this in more detail.

Selectivity of migration on income and wealth

The a priori considerations provided above paint a mixed picture of the role that income and wealth play. The following emerge:

  • Higher wealth allows people to fund their move more easily.
  • On the other hand, less wealth means people have less to lose and are more desperate to migrate.
  • Huge wage gains attract more migration. But huge wage gains in absolute terms are linked to higher incomes, whereas huge wage gains in proportional terms are linked to lower incomes.
  • Higher wealth may be correlated with other traits that predict greater or lesser ability to migrate. This is particularly the case for self-acquired wealth, but might also apply for inherited wealth to the extent that parental wealth correlates with parental attributes and via that with the person’s attributes.

As noted above, the nature of the income and wealth pattern may matter more than the amount. People whose income and wealth is heavily tied to their current location are likely to stay, whereas those whose income and wealth are tied to transportable skills or assets are more likely to move to places where their skills and assets can be best used to earn more.

One example of a “wealthy with little to lose” combination is (relatively) wealthy members of minority groups that are forcefully evicted as path of ethnic cleansing, or anticipate that this will happen. This was the case with Indians in Uganda, businessmen who found themselves on the wrong side of the border in the runup to the Partition of India, Tamils in Sri Lanka, and many others. Market-dominant minorities may in general fear hostile political environments and may be eager to leave when populist political parties or opinions are ascendant.

What does empirical evidence suggest about the relation between income/wealth and emigration? This blog post by Michael Clemens reviews the evidence and concludes that for countries below something like $6,000–8,000 GDP per capita (at US prices), countries that get richer have more emigration. The plot of emigration flow in terms of GDP per capita peaks at this income range, as does the plot of emigrant stock in terms of GDP per capita. Clemens writes:

Social scientists have six theories for this “mobility transition”. I review these theories and the evidence for them in the paper. Briefly: 1) Development is usually accompanied by a demographic transition that favors a corresponding mobility transition, 2) development means that more people can afford to emigrate, 3) development means that more people can access the information they need to emigrate, 4) development tends to disrupt economic structures that keep people immobile, 5) development shapes domestic inequality in ways that foster migration, and 6) development in country A means that people in country B are more likely to give visas to migrants from A.

The Zelinksy model of mobility transition is also relevant.

Selectivity of migration on criminality

The following are some considerations:

  1. The strong future orientation needed to migrate suggests that migrants will be less criminal, because crime generally involves short-term benefits and long-term costs, and criminals generally discount the future heavily. In addition to future orientation, the ability to execute the move might also filter for other relevant positive traits that predict lower criminality.
  2. The fact that migrants are likely to have more money (in order to fund their moves) and the fact that richer people commit fewer violent and property crimes, argues in favor of migrants being less criminal.
  3. The fact that migrants often need to cheat and lie in their visa applications in order to be able to migrate, or that they cross borders illegally, might lead to migrants being selected for higher levels of criminality.

In a later post series on crime and open borders, we’ll weigh these considerations against one another. The general bottom line will be that emigrants have substantially lower crime rates than natives of their source countires, and this is attributable in large part to selection.

Selectivity of migration on enterprisingness

People who move have strong future orientation, adventurousness, openness to experience, and willingness to take risks. This suggests that they are more likely to be enterprising in the general sense. In some cases, this translates to being more entrepreneurial (see here for more on existing research). The following are some other considerations:

  • To the extent that regulations on migrants make it easier for them to stay in standard, steady jobs, they are less likely to engage in entrepreneurship. This is a major issue for migration to the US: it’s much easier for high-skilled migrants to get a work visa working at a big company than to start a company. Note that this effect could operate at both a selection and a treatment level: entrepreneurial people may shy away from migrating to a place where it’s not that easy to start a business, and people who’ve already migrated may prefer to continue in an existing company than start a business.
  • To the extent that regulations (or societal discrimination) inhibit work in the formal sector, migrants are more likely to start their own small businesses. For instance, it may be easier for families to start a restaurant and have family members work at it so that younger members can contribute and they can circumvent labor laws. Note that this type of entrepreneurship isn’t the “create a billion-dollar business” type, and has lower value per entrepreneur, but it is still important to society. At the same time, artificial restrictions on formal sector employment may lead to too many family businesses and a more inefficient economy overall because family businesses cannot avail of the economies of scale.
  • The amount of wealth that migrants have affects whether they can afford to experiment with entrepreneurial ventures. As we saw, the relationship between migration and wealth is unclear.

Selectivity of migration on political attitudes

While there are many migrants who leave because of political persecution, this political persecution often has more to do with ethnic identity and religious beliefs than with specific political beliefs. (There is some relation between religious beliefs and political beliefs, but it’s very tenuous). The following are some general remarks:

  • The very fact that migrants left their home country suggests that they are not overly attached to the institutional or policy framework of that country. This doesn’t mean they actively dislike it. This creates a prior against migrants replicating the policies of their home countries. Empirically, there is little evidence of home country policy replication: people from communist countries aren’t noticeably in favor of communism and don’t seem to want to impose communism on other countries. At any rate, they haven’t been successful doing so. On a related note, see Ilya Somin’s blog post on immigration and political freedom.
  • People who have a strong aptitude or interest in politics (in the sense that they want to become political activists or politicians) are likely to stay in their home countries, because it’s easier to make headway in politics as a native.

Remarks about the distinction between selectivity with respect to source and target countries

The arguments above concentrate on what we expect regarding selectivity relative to the migrants’ source countries, because we’re trying to answer the question: of a given set of people in a given environment, who’d be most willing and able to leave? But people in the receiving countries are more interested in comparing immigrants to natives, in order to figure out how immigration affects the overall societal composition.

To what extent can the above arguments make predictions about how immigrants compare with natives? We need to know both how much the countries differ (the (1) versus (2) gap) and how large the treatment effect of migration is (the (3) versus (4) gap).

For instance, let’s say we have a low-productivity poor country A and a high-productivity rich country B. By our general arguments, we think that the people who migrate from A to B are likely to be more enterprising, more future-oriented, and more adventurous than those who stay behind in country A. How do they compare with country B? The conclusion we draw depends on what we think of the relative levels of these traits in the two countries.

One school of thought is that the distribution of traits in the populations of both countries is similar, so that the (conjectured) fact that emigrants do better on these traits than natives also implies that immigrants will do better on these traits. For instance, one might argue that there isn’t any difference between the levels of future orientation in China and Taiwan. Therefore, immigrants from (low-income) China to (high-income) Taiwan, who are selected relative to their source country with respect to future orientation, are probably also selected relative to their target country.

Another school of thought is that the reason country B is richer and has higher productivity is that the people there are more enterprising, more future-oriented, more adventurous, etc. For instance, one might argue that the United States is more entrepeneurial than the United Kingdom, and this accounts for the difference in their per capita levels of income and wealth. In this case, even though emigrants from country A score higher on these traits than natives of country A, it’s unclear how they compare with natives of country B. There are two separate issues to consider to figure this out:

  • How strong is the selection effect of migrants relative to their source countries, in comparison with the difference between source and target countries? Even if the US is more entrepreneurial than the UK, that difference on average might be much smaller than the selection effect for migrating.
  • How much of a treatment effect is there on migrants? The strength of the treatment effect arguably depends on the age of migration. Those who migrate as young children, and do not grow up in an isolated culture, are likely to be exposed to similar cultural influences as the natives of the target country, though they still experience a different home culture and prenatal environments, and are genetically close to country A. Note that though treatment effects are stronger for young people, selection effects may be weaker, because young people are often dragged along by their parents rather than being active participants in the decision to move.

Remarks on differences in selectivity of different migration policy regimes

The extent of selectivity depends heavily on the nature of the migration policy regime. Thus, the level of selection under open borders is likely to be quite different (and in general, much weaker) than the level of selectivity under the status quo.

The majority of the considerations outlined in this post apply to migration even under open borders. The main difference is that rigid legal constraints on whether one can migrate, and the amount of bureaucratic red tape one has to go through to migrate, both reduce under open borders. If we are trying to quantitatively ballpark the level of selectivity, we need to keep in mind its sensitivity to the policy regime. In a future post, I’ll explore ways that governments can (and do) affect the selectivity of migration through explicit migration policy.

A conceptual framework for empirical analysis of migration (part 4: models for migrant performance)

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This post is part 4 of a series outlining a conceptual framework for the empirical analysis of migration. Read the introductory post to the series here, part 1 here, part 2 here, and part 3 here.

Migrant performance as a combination of source and target country performance?

A simple model against which we could compare reality is that migrant performance is a function of the native performance in their source and target countries. In other words, if we knew the performance of source country natives and we knew the performance of target country natives, we would be able to predict how migrants perform.

Qualitatively, here are some possibilities:

  1. Migrant performance falls somewhere in between the performance of their source and target countries. For instance, perhaps the performance of migrants falls midway between the source and target countries. Note in particular that if the source and target countries have identical values for natives, then migrants are also identical to them, suggesting that there is no effect coming from being a migrant per se.
  2. Migrant performance is nearly identical to that of natives in the target country, and is independent of the source country.
  3. Migrant performance is nearly identical to that of natives in the source country, and is independent of the target country.
  4. Migrant performance is determined by performance in the target country, but is not equal to it. For instance, perhaps migrants have incarceration rates that are 0.7 times the incarceration rates of natives in the target country, regardless of their source and target countries.
  5. Migrant performance is determined by performance in the source country, but is not equal to it. For instance, perhaps migrants have fertility rates that are 1.2 times those of their source countries, regardless of where they come from and where they go.

Mathematical digression: a linear combination model

As in part 1, denote by $latex x_{ij}$ the performance of migrants from country $latex i$ to country $latex j$ on indicator X, and denote by $latex x_{ii}$ and $latex x_{jj}$ respectively the performance of natives of the countries who stay put. We claim that, to a reasonable approximation, there is a (nice enough) function $latex F$, independent of $latex i$ and $latex j$, such that:

$latex x_{ij} = F(x_{ii},x_{ij})$

The simplest possible example of such a function is a linear combination. In this model, we have the following, where $latex \alpha$ and $latex \beta$ are nonnegative reals:

$latex x_{ij} = \alpha x_{ii} + \beta x_{jj}$

We now revisit the five cases above in terms of the linear combination model:

  1. $latex \alpha + \beta = 1$, i.e., the performance of migrants is a convex combination of that of natives from the source and target countries, and therefore in particular lies somewhere in between those two values. In that case, we can write $latex x_{ij} = \alpha x_{ii} + (1 – \alpha) x_{jj}$. The special case $latex \alpha = 0.5$ is the one where migrant performance is midway between the natives of the source and target countries.
  2. $latex \alpha$ is close to 0 and $latex \beta$ is close to 1.
  3. $latex \alpha$ is close to 1 and $latex \beta$ is close to 0.
  4. $latex \alpha$ is close to 0 and $latex \beta$ is positive but not close to 1.
  5. $latex \alpha$ is positive but not close to 1, and $latex \beta$ is close to 0.

Linear models are not the only ones possible: one can imagine more complicated functional relationships, including power relationships (which would be linear once you take the logarithm). Linear models are the ones people generally look for when predicting performance, and that’s what linear regressions are generally used for. Anyway, the best type of model to use depends on the type of indicator we have and what we understand about how it’s determined, i.e., we need a phenomenological story first (more on this later in the post).

End mathematical digression

Separating selection and treatment: potential migrant performance and actual migrant performance in terms of source and target country performance

The above discusses the performance of people who actually migrate in terms of their source and target countries. But, building on the discussion in part 2 and (more directly relevant) part 3, we’re also interested in how potential migrants would perform if they weren’t allowed to migrate. This allows us to separate out the selection and treatment effects.

Unlike the case of people who do migrate, it’s not a priori clear why the indicator value in the target country should be a predictor for people who don’t migrate. One argument that it should: the very fact that they are considering migration to the target country, or that a potential migration policy is considering them, suggests potential affinity with the target country. It may happen in some cases that the function doesn’t depend on $latex x_{jj}$ at all.

Mathematical digression: two linear combinations

To stay similar to the earlier notation (from parts 2 and 3 of the series), we denote the “how migrants would do if they were’t allowed to migrate” quantity as $latex x_{ij}^{n,o}$. We are thus interested in understanding the function $latex G$ such that:

$latex x_{ij}^{n,o} = G(x_{ii},x_{jj})$

The simple case is a linear function, i.e., we have:

$latex x_{ij}^{n,o} = \alpha^{n,o}x_{ii} + \beta^{n,o}x_{jj}$

We can now make cases based on the values of these numbers. We list some possibilities:

  • Suppose $latex \alpha/\beta < \alpha^{n,o}/\beta^{n,o}$. This means that for people who do migrate, their performance is predicted more by the target country than if they were not allowed to migrate.
  • $latex \beta^{n,o} = 0$ suggests that the performance of potential migrants, if they stay in their source country, is determined completely by their source country. In the case $latex \alpha^{n,o} = 1$, the potential migrants are indistinguishable on the indicator from others in their source country. In other cases, migrants differ from others in their source country, but by a constant factor.
  • $latex \alpha = 0$ suggests that the performance of people who actually migrate is determined completely by their target country. In the case $latex \beta = 1$, the migrants become indistinguishable from natives of the target country. In other cases, they differ by a constant factor.
  • If $latex \alpha < \alpha^{n,o}$ and $latex \beta < \beta^{n,o}$, that implies that migrants score lower on the indicator if they're allowed to migrate than if they're not, regardless of how the source and target country compare on the indicator. The opposite conclusion holds if $latex \alpha > \alpha^{n,o}$ and $latex \beta > \beta^{n,o}$.

End mathematical digression

Phenomenological stories

The above were purely mathematical models of migrant performance, and didn’t provide a story as to why a particular functional expression works, of why particular parameter values are right. But what’s going on? Why might we expect a functional relationship, linear or otherwise, between migrant performance and the performance of natives in the source and target countries?

Some possible stories:

  1. Migration policy explicitly selects for people based on how they fare relative to the native population of the recipient country, so that the similarity across countries between the relative performance between natives and migrants is largely because most countries’ migration policies revolve around similar explicit objectives in terms of how the migrants should compare with the natives.
  2. Immigrants self-select for countries where their performance will be at a particular level relative to natives.
  3. People self-select to emigrate if their performance relative to their source country is at a particular level relative to the natives of that source country.
  4. People’s intrinsic characteristics (that they transport with themselves when they migrate) only determine their performance relative to where they live, rather than in absolute terms. For instance, a person’s inclination to criminality may determine how much crime the person commits relative to natives of the region. Similarly, a person’s skill level may determine how much money the person can earn relative to natives of whatever country he or she is in, rather than in absolute terms.

Mathematical digression: translating the phenomenology to the linear combination model

(1) and (2) explain the parameters $latex \beta^{n,o}$ and $latex \beta^n$. (3) explains the parameters $latex \alpha^{n,o}$ and $latex \alpha^n$. In the extreme case that (4) holds completely, $latex \alpha^{n,o} = \beta^n$ and $latex \beta^{n,o} = \alpha^n = 0$.

End mathematical digression

A conceptual framework for empirical analysis of migration (part 3: simplified model assuming no changes to non-migrants)

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This post is part 3 of a series outlining a conceptual framework for the empirical analysis of migration. Read the introductory post to the series here, part 1 here, and part 2 here.

The model in part 2 for comparative statics was extremely complicated. The problem was that there were too many moving parts: there was a selection effect arising from differences in grouping, and there was a treatment effect arising from changes in migration patterns affecting both the marginal migrants and others. This part of the series considers a simpler model. Our first pass at exposition will lay out a very simple toy case, and we’ll then discuss variants and possible ways of ramping up the complexity.

We’ll keep focus on two countries: country A (a source country for migrants) and country B (a target country for migrants). We’ll assume there are no reverse migration flows, and no other countries to compete as sources and targets for migrants. We are considering a migration policy that would allow a subpopulation of country A to migrate. We have three relevant subpopulations:

  • A subpopulation of the population of country A that comprises the would-be migrants under the migration policy of interest. We’ll call these people the potential migrants.
  • The remaining population of country A, that would not migrate with or without the migration policy of interest.
  • The resident population of country B.

We are thus comparing the no-migration scenario with the scenario where an identified subpopulation of country A is allowed to migrate to country B, and takes advantage of the opportunity.

We are interested in providing a rank-ordering and quantitative comparison for the following four quantities:

  1. Performance of natives of target country B on indicator X.
  2. Performance of natives of source country A (who would not move under either policy) on indicator X.
  3. Performance of potential migrants on indicator X if they were allowed to migrate (i.e., in the migration scenario).
  4. Performance of potential migrants on indicator X if they were not allowed to migrate (i.e., in the no-migration scenario).

Note that:

  • The difference between (2) and (4) measures the selectivity of migration relative to the source country. In other words, it measures emigrant selectivity.
  • The difference between (1) and (3) measures the selectivity of migrants relative to the target country, or equivalently, to their failure of assimilation (the assimilation may be “upward” or “downward” depending on how the migrants compare with the target country natives). In other words, it measures immigrant selectivity.
  • The difference between (3) and (4) refers to the treatment effect of migration on migrants. In other words, it measures the premium of migrating.

Aspects of the rank ordering that matter from various normative perspectives

The following hold prima facie (here, weighted averages refer to averages weighted by population size):

  • The individualist universalist cares mainly about the comparison between (3) and (4), because that’s the main source of change to individuals.
  • The universalistically inclined analytical nationalist, who cares about how national averages change rather than how individuals do, cares about how (1) compares with the weighted average of (1) and (3) and how the weighted average of (2) and (4) compares with (2). Due to compositional effects, this is not always in agreement with the individualist universalist perspective. In particular, compositional effect paradoxes arise under rank orderings (1) > (3) > (4) > (2) and the reverse ordering (2) > (4) > (3) > (1). In words, (1) > (3) > (4) > (2) means that the migrant subpopulation is better at the indicator than the source country, that migration improves it further, but that even after that improvement, they still fall short of the natives of the target country.
  • A person driven by local inequality aversion cares about how the gap between (1) and (3) compares with the gap between (2) and (4) (and also the magnitude of migration relative to source and target country populations).
  • Assuming that the performance of people on indicator X affects the well-being of others in the territory (this is true for indicators such as crime), the citizenists and territorialists for country B care about how (3) compares with (1).
  • Assuming that the performance of people on indicator X affects the well-being of others in the territory (this is true for indicators such as crime), the citizenists and territorialists for country A care about how (4) compares with (2).

Recall that there are some rare indicators (such as resource use) where we care about the total rather than the average. For instance, in a country where water is scarce, we may care about total water use rather than per capita water use. In this case, we also need to know the relevant population sizes, and some of the prima facie claims above do not apply.

Mathematical digression: matrix description

Suppose country 1 is country A and country 2 is country B. Following the notation for part 2, our matrix for indicator X under the no-migration scenario, which we call the old scenario, is:

$latex \begin{pmatrix} x_{11}^o & \text{undefined} \\ \text{undefined} & x_{22}^o \\\end{pmatrix}$

Our matrix for indicator X under the migration scenario, which we call the new scenario, is:

$latex \begin{pmatrix} x_{11}^n & x_{12}^n \\ \text{undefined} & x_{22}^n \\\end{pmatrix}$

Note that we do have $latex x_{22}^n = x_{22}^o$, because the set of people is the same in both cases and the individual indicator values are the same for each of them. On the other hand, we do not necessarily have $latex x_{11}^n = x_{11}^o$. This is because even though all the individuals who stay put in country A under both scenarios fare the same under both scenarios, the no-migration scenario also sees the potential migrants stay put, thereby affecting the average value of the indicator (the compositional selection effect).

What we’re really interested in is the matrix:

$latex \begin{pmatrix} x_{11}^{n,o} & x_{12}^{n,o} \\ \text{undefined} & x_{22}^{n,o} \\\end{pmatrix}$

This uses the groupings from the migration scenario (i.e., it separates the source country population into those who stay put and those who migrate in the migration scenario) but using indicator values from the no-migration scenario. We want to compare this with the migration scenario matrix:

$latex \begin{pmatrix} x_{11}^n & x_{12}^n \\ \text{undefined} & x_{22}^n \\\end{pmatrix}$

Our conditions now tell us that $latex x_{11}^{n,o} = x_{11}^n$ and $latex x_{22}^{n,o} = x_{22}^n = x_{22}^o$. Therefore, the two matrices above coincide except in the top right entry. In other words, we’re looking at these two matrices:

$latex \begin{pmatrix} x_{11}^n & x_{12}^{n,o} \\ \text{undefined} & x_{22}^n \\\end{pmatrix}, \qquad \begin{pmatrix} x_{11}^n & x_{12}^n \\ \text{undefined} & x_{22}^n \\\end{pmatrix}$

We can now see the four numbers that we were attempting to rank-order and compare quantitatively: $latex x_{11}^n$ (this is (2) in the list), $latex x_{12}^{n,o}$ (this is (4) in the list), $latex x_{12}^n$ (this is (3) in the list), and $latex x_{22}^n$ (this is (1) in the list).

Adaptation to migration liberalization and marginal migration

For simplicity, the above analysis considers the no-migration scenario as one extreme. It can be adapted to a comparison of liberalizing an existing migration policy towards a subpopulation. We would then be interested in the question of marginal migrants: the additional people who can migrate under liberalization. However, there are complications introduced by the distinction between marginal and average: the average performance for the existing set of migrants who migrate under the less liberalized policy may differ from that of the performance for set of migrants who migrate under the more liberalized policy. The difference could be a difference in composition (selection effect) or a difference in treatment.

The place premium: an example

The place premium measures the gap (in proportional terms) between (3) and (4), i.e., the treatment effect of migration on migrants. It is one of the few such measures that people have attempted to compute for a wide range of source and target countries; see for instance this working paper by Clemens, Montenegro, and Pritchett that has computed place premium tables on Page 11.