Yearly Archives: 2013

How Did We Get Here? The Origins of Immigration Restrictions: Intro

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As Vipul Naik has recently commented on, I am going to be starting a new series of posts here on  Open Borders. The goal of this series will be to examine how border restrictions have changed and what arguments were used to justify the new rules. Border restrictions of various sorts do have long histories, but why does a more open system tend to close up or a closed system become more open? How do the arguments made in the past compare to modern immigration arguments? Did those arguments hold up given the information available at the time? Do they hold up better or worse knowing what we know now? And in cases where dire predictions for or against immigration restrictions were made, how well did those predictions hold up?

This discussion can help move discussion away from a status quo bias. All else being equal, people tend to prefer the status quo to a change. This is very often a good thing. Indeed, the precautionary principle would indicate that the burden of proof should lie with new policies that they are not harmful. As an example, if you don’t know whether doing exploding a bomb will blow up the planet, but you think it might, then the safe action to take would be avoid blowing up that bomb. However, this principle holds less weight when the reason a status quo is in place to begin with is because of faulty reasoning and that status quo causes great harm itself. We have lots of examples on this site of how current policy creates lots of harm for the world be preventing what we could otherwise achieve or maintaining a status quo that isn’t working for hundreds of millions, but were there good reasons to put the restrictions in place to begin with? Did periods of greater immigration cause serious problems avoided by restriction? And have immigration systems been set up well given the concerns which motivated their creation? Here’s where historical examination and this series of posts in particular come in. I’ll be looking at the arguments used at the time and try to determine which made sense, which were over blown, and which were complete rubbish. Historically, all sides in immigration discussions have made mistakes, screwed up predictions, or even stated outright lies. Such is the nature of politics. But has one side or the other tended to be closer to the truth? If so, shouldn’t we be more suspicious of arguments from the opposite corner? If not, then at least we gain perspective that arguments for and against immigration have been equally bad and that the current status quo (whether one thinks too many or too few immigrants are allowed in) was established with shaky reasoning.

In any event, I hope to cover topics I already know some about such as the closing of the US border, Roman and early feudal restrictions, the end of passportless borders in Europe during World War 1, the partial re-opening of the US border starting in 1965, and the establishment of the open border Schnegen Area in Europe. If any of you readers have suggestions for other examples for me to look into please leave them in the comments and I’ll see what I can dig up! The first real post in this series will deal with the Chinese Exclusion Act of 1882 and when that goes up I’ll give a link in this post as well. Given that this kind of project takes quite a bit of time and that I am trying to keep sources mostly limited to data available online and in English (an unfortunate restriction but one that helps keep the conversation accessible to as many readers as possible), I’m always open to sources you all find! For the upcoming post the major sources I intend to use can all be found under the primary and secondary source sections of this page. So if there’s a decent source (whether primary or secondary…I figure my need for tertiary sources is probably met in most cases by Wikipedia), let me know in the comments.

Bleg: research on the effects of open borders beyond the labor market

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The double world GDP literature cited in Clemens’ paper (and also John Kennan’s paper) provides estimates of how free global labor mobility would affect world GDP, mainly through their effects on the labor market (though other channels of effect are also considered in these papers, albeit perhaps not as much as they should be). But I don’t know of any literature about the effect that open borders might have on crime (something I speculated about here), global IQ (something I asked Bryan Caplan to bleg), and global politics (whether through political externalities in the receiving countries or a changed political landscape in the immigrant-sending countries). Speculation about the effects on the dating and mating markets and the genetic composition of future generations might also be quite valuable (see for instance Erik’s comment).

If a serious case is to be made for open borders, and if serious efforts are to be made to move towards open borders with appropriately designed keyhole solutions, it is essential to understand, envisage and prepare for a range of scenarios regarding these questions.

So, I’m blegging for the answers to two questions:

  1. If you’re aware of any literature that considers counterfactual scenarios of radically more open borders, whether locally (for specific country pairs) or globally, but that goes beyond simply measuring the effects on the labor market, please pass it on in the comments.
  2. Assuming that I am correct about the paucity of such research, though, why is there so little research on these topics, even compared to economics research on the effects of open borders? Two hypotheses have been suggested to me:
    • Nathan Smith’s view: Various frameworks in economics, such as rationality, allow for the consideration of radical counterfactual scenarios in a manner that is not necessarily realistic but still bears some semblance of objectivity and offers some type of ballpark. No similar widely-agreed-upon first-pass framework exists in other disciplines.
    • Bryan Caplan’s view: Economics manages to attract a few people who are genuinely curious and adventurous and willing to consider radical alternative scenarios and perform a serious analysis of these scenarios. Other disciplines may not attract such people.

    Any alternative hypotheses would also be welcome.

US to foreigners: we’re a nation of immigrants! (If you’re a lottery winner, or Methuselah)

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I recently stumbled across this interesting blog post by immigration lawyer Angelo Paparelli, where he talks about US visa refusals. The post is from 2009, responding to then-Secretary of State Hillary Clinton’s public statement that she was committed to streamlining the US visa process. Angelo mentions a staggering figure from the State Department’s fiscal year 2008 annual report:

In FY 2008, the State Department’s consular officers denied 1,481,471 nonimmigrant visa (NIV) applications under Immigration and Nationality Act (INA) § 214(b) (failure to establish entitlement to the requested NIV classification). While 19,837 (1.3%) of these refusals were overcome, almost 99% of the refusals prevented possibly deserving applicants from coming to the United States. [Note: These do not include the 64,516 refusals for specific grounds such as criminal conduct, public charge, material support of terrorism, etc.]

I checked the 2012 fiscal year figures and they are similar in every meaningful respect. To calculate the approval rate we need to bring in data on visas issued: with 8.9 million non-immigrant visas issued and 1.4 million non-immigrant visa applications rejected (virtually all because of 214(b)), we get an overall rejection rate of about 14%. I don’t know if that is too high or too low. But look at the data for yourself: these aren’t people with communicable diseases or criminal records. Over 1 million people have been refused student or visitor visas for the amorphous reason of “Failure to establish entitlement to nonimmigrant status.”

Presumably the intent is to deter fraud: there is a valid concern that non-immigrant visas can be used to get into the country and via overstaying, unlawfully “convert” the visa-holder to a de facto immigrant. But the main reason that is a problem is because the immigrant visa process itself deters bona fide immigrants! If you don’t believe this, one of Angelo’s colleagues recently crunched the numbers on current expected waits for some classes of lawful immigrants:

The wait for someone getting a visa today was as long as 24 years. The wait for someone starting today is much longer. An extreme example is Mexico F2B [Mexico-born “Unmarried Sons and Daughters (21 years of age or older) of Permanent Residents”].

The last time I took the difference between the cut-off date and the present date, then factored in the rate of “advance,” the anticipated delay for someone applying today under that category was 395 years. Mexico F-1 [Mexico-born “Unmarried Sons and Daughters of U.S. Citizens”] was “only” about 80-85 years.

In the US, gun rights activists love to say that if you make guns outlawed, only outlaws will have guns. By outlawing immigration, the US has ensured only outlaws will immigrate. Abortion rights activists love to warn that if abortions are banned, the only thing that will change is that more women will get hurt or die from unlicensed backdoor abortion providers: if immigration is banned, unsurprisingly millions will risk life and limb to immigrate.

If wait times longer than the human lifespan are not a de facto ban, I don’t know what is. You might as well tell someone he can own a gun when he lives to be as old as Methuselah (a man from the Old Testament who lived for over 8 centuries), or tell her she can have an abortion when she wins the Powerball (an American lottery). You may scoff. But that is exactly what the US government tells the person looking to join their family or earn a honest living. “Sure, we’re a nation of immigrants! If you’re a lottery-winning Methuselah, come on in.” And it is worse for those 1 million+ people denied the chance to visit or study in the US: because the US government has essentially outlawed immigrants, it has similarly had no choice but to do the same for visitors too. Through no fault of their own, millions of foreigners have been punished for the US government’s failure to fix its own laws.

Prediction records and open borders

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I recently finished reading The Signal of the Noise by prediction guru and stats wizard Nate Silver (here’s the book on Amazon, and here’s Silver’s FiveThirtyEight blog-cum-website). Silver is well known for his extremely accurate predictions and commentary related to US elections, but his knowledge of and interest in issues related to prediction range far and wide. His book deals with many subtleties associated with prediction. The book manages to go quite deep into the statistical issues without pulling any punches, yet manages to be broadly accessible to readers.

Silver does not discuss anything as radical as open borders, and in general, does not discuss normative questions at all, preferring to stick to his area of expertise: the accuracy and precision of predictions and forecasts and the problems associated with trying to make good predictions and forecasts. Nonetheless, my guess after reading Silver’s book is that he would be extremely skeptical of any claims regarding the effects of open borders, which are way “out of sample.” In particular, I’m guessing Silver would be unimpressed with claims that open borders would double world GDP. At any rate, reading Silver makes me more skeptical of claims made about the effects of open borders with allegedly high confidence. If you believe in Knightian uncertainty as a concept, you may well take the view that the uncertainty associated with open borders is Knightian in nature, and that most attempts at quantifying its impact are flawed. This might also explain why, even though there is a broad economist consensus supporting somewhat more open borders, few economists commit to going all the way to open borders. My co-blogger Nathan noted this explicitly in a comment on another blog post.

Even in areas where we are looking at “out of sample” predictions, however, all is not lost. One idea that Silver repeatedly reiterates throughout his book is that one should keep and use every piece of data. Judging the effects of open borders might be very difficult, and we may end up with a huge range (i.e., low precision). But we can still use some data points. The type of question that somebody like Silver, starting from the outside view, would ask is: “Of the people making predictions regarding the effects of changes in migration policy regimes, who has the better prediction track record?” Or “of the various methods used to predict the effects of changes in migration policy regimes, which methods have the better prediction track record?” Ideally, what we’d need to make this kind of judgment is:

  • A large number of data points,
  • all of which have outcomes that can be agreed upon clearly,
  • with information about what prediction each side made prior to the event, and
  • with information about what the outcome was.

Weather prediction is one such example. There are a large number of data points (the daily maximum and minimum temperature and precipitation statistics in many cities over half a century). The final value of each data point is broadly agreed upon, though there are measurement error issues. The values predicted by organizations such as the National Weather Service and Weather Channel are also available. All the conditions for an analysis are therefore available, and Silver in his book mentions one such analysis. The analysis finds that both the National Weather Service and the Weather Channel are fairly accurate, but that the Weather Channel (deliberately, it turns out), inflates the probability of precipitation on days when that probability is extremely low. This phenomenon is now known as wet bias.

Predictions in the political and economic realm don’t fare as well. There are a reasonably large number of data points regarding the outcomes of various electoral races, which satisfy the necessary conditions (lots of data points, clear outcomes, information about each side’s predictions, and information about the outcome) that allow us to get a sense of the quality of political predictions. The data isn’t as extensive as for weather, but it is still quite extensive. Silver finds that while predictions that relied on statistically valid polling techniques tended to do well, predictions made by political pundits on television didn’t. Silver finds a similar disappointing story of prediction when it comes to economic forecasting. He is also critical of people who make predictions and forecasts without specifying the margin of error or the distribution, but simply give a point estimate. In the discussion, Silver alluded to Tetlock’s study of prediction records and his distinction between “foxes” and “hedgehogs” (see here for an article co-authored by Tetlock with a summary of the idea).

When two sides are debating an issue and relying heavily on empirical claims about the future to make their respective cases, you’d naturally be curious about the prediction records of the two sides with respect to past predictions. There are two additional complications over and above the obvious measurement difficulties that apply particularly to political debates such as migration policy debates:

  • The specific people engaging in the debate are usually different each time. Most pro-immigration groups and people around today weren’t there when the Immigration and Nationality Act of 1965 was passed. The same is true of the anti-immigration groups and people. Given this complication, each side can happily claim allegiance to the correct claims made historically by their side, and disown the incorrect claims as having been made by others they don’t support. This can be partly overcome by trying to come up with objective metrics of just how similar arguments offered today are to the failed arguments of the past, but there are many then versus now “outs” to deflect claims of objective similarity between the present and the past.
  • Relatedly, it can be argued that proponents of an argument weren’t saying it because they actually believed it, but rather, they were just trying to rally public support to our cause, knowing that they would need to lie to (or at any rate, exaggerate their case to) a public that did not share their normative views. (I discussed incentives to lie about immigration enforcement in an earlier post).

Although these two difficulties present a challenge, there is probably much to be gained from a retrospective analysis of past changes in migration regimes and the predictions made by various people during those changes. Significant changes are better because (a) more people are likely to make explicit predictions of the effects of significant changes, and (b) the larger effect size makes it easy to determine what actually happened. Unfortunately, significant changes are also fewer in number, so we do not have the “large number of data points” that would allow for good calibration of the accuracy of predictions. But we’ve just got to deal with that uncertainty. It’s better than completely ignoring the past.

Relatedly, looking at migration regime changes sufficiently far back in the past also gives us some idea of the more long term effects of the changes. BK, one of the skeptics of open borders in our comments, has argued that the benefits of migration are front-loaded, while the costs take decades to unfold (see for instance here and here). Evaluating such concerns would require us to look at the long-term effects of past migration regime changes.

My co-blogger Chris Hendrix plans to begin a series that looks at various instances of open borders becoming more closed, along with the predictions and rationales offered at the time (expect to read Chris’s introductory post soon!). Later, one of us (perhaps Chris again, perhaps I, or perhaps one of our other bloggers) will be looking at instances of immigration liberalization and the predictions and arguments accompanying and opposing them. I’m particularly interested in the Immigration and Nationality Act of 1965 in the United States and the Rivers of Blood Speech by Enoch Powell in 1968 in the UK. The historical analysis will hopefully help us better calibrate the accuracy of predictions and forecasts about changes to migration regimes, hence better enabling us to evaluate the plausibility of claims such as “double world GDP” or end of poverty from the outside view.