Tag Archives: double world GDP

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

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.

Prediction records and open borders

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.

Skirting Around the Restrictions: Will Technology Make Borders Obsolete?

The rise of modern communications technology has drastically changed the way humans interact with each other. Physical distance matters less than ever. You my dear reader may be seeing this post of mine from 10 minutes away from my apartment or from 12,000 miles away. Indeed the difference in time which you might theoretically be able to first read this is insignificant between those two locations. Compared to times when it took six months to traverse the silk road from Europe to China that is absurd. And this technology is not limited by borders (with some important exceptions, though just like real borders people find ways to sneak around that). Looking at the author list for this site even it’s possible to find people from across the globe writing about open borders. Technology might be beating us to the punch on open borders (for a similar argument that poverty might end before we open the borders see Vipul’s earlier post). So if this is all true does this mean there’s no point to open borders advocacy? Has technology already won the battle for us?

Sadly this post doesn’t end with me cracking open a bottle of champagne and celebrating victory (or maybe just a beer, champagne isn’t really my thing…anyways…). Continue reading “Skirting Around the Restrictions: Will Technology Make Borders Obsolete?” »

The media makes the case for open borders

Well, not quite. But a better lifting of the global Rawlsian veil there never was. Citing a study by The Economist, the Washington Post published this map of the best countries in the world to be born in today (the bluer the better):


The summary of the results is worth reading, but there were a couple money quotes:

Even Portugal and Spain, for all their very real troubles, score highly. A child born today is likely to have a better life, according to the data, in Poland or Greece — yes, Greece — than in rising economic giants such as Brazil, Turkey or China.

Though countries such as Indonesia and Vietnam are projected to show astounding economic growth over the next generation, they are poor today. This map is a reminder that being born into a poor society, even one that offers opportunities for new wealth, can still mean life-long challenges.

So, if you’re a Westerner fretting about American decline or European collapse, then if nothing else, know that your children have still lucked into one of the best deals in history: being born in the right place at the right time.

Being born in the right place at the right time counts for a lot. There’s nothing ironclad that makes the amount of people being born in Portugal or Greece or Australia or the US today the right amount. If I took ten babies from Bangladesh and dropped them off in Germany tomorrow with forged German citizenship papers, in what conceivable way could their presence harm anyone there, growing up as German as can be? Yes, there is in principle some limit to how many people a country can have, and coming up against that constraint is a plausible reason to enforce immigration restrictions. But adopting restrictions without bothering to prove such a limit has been reached is nothing more than creating a new aristocracy.

Putting aside difficult-to-quantify social factors for now, from a purely economic standpoint, the global aristocracy of birthplace is immensely inefficient. How inefficient? The most conservative estimate is that true open borders would make humankind 67% richer. The most aggressive estimate suggests it would make us 150% richer. We’re talking doubling world GDP, folks. Even if you make allowance for social frictions necessitating some immigration restrictions, there is absolutely no rational basis for believing the economically rational thing to do is to, as a general rule, only have people live and work in the country of their birth.

Much of what I am today, I owe to my parents and my country, and to my creator who made me who I am. But I also owe an immense amount to studying and working in the United States, which literally offered me opportunities no other country could give me. I was lucky enough to be born in circumstances that could get me to the US. How many billion others can say the same?

It’s one thing to punish someone because if you don’t, they will harm you. That is at least prima facie plausible. But it’s another thing to punish someone purely for an accident of birth out of their control. I had no choice in where I was born. Neither did you. Let’s be glad we were born in pretty good circumstances (because if you’re able to read this, you’re almost certainly one of the luckiest people alive). But let’s not use birth as a reason to deny those less fortunate than us some of the same opportunities you and I had.

John Kennan’s “Open Borders”

This post is going to attempt to do something difficult, namely: bring a contribution to technical economic theory within reach of lay readers. The typical lay reader, or for that matter even an atypically intelligent reader who is not a specialist in economics, could understand little of Kennan’s paper, or for that matter most academic economics papers. I don’t totally understand the paper either, but I think I mostly understand it. I’m pretty sure I understand the main thrust. The work in question is “Open Borders” by John Kennan. If one had to pick one thing to stick in a newspaper headline, it would be Kennan’s prediction that

For the 40 countries in Figure 6 this gives an estimate of $10,798, per worker (including nonmigrants), per year (in 2012 dollars, adjusted for purchasing power parity). This is a very large number: the average income per worker in these countries is $8,633, so the gain in (net) income is 125%. For all of the countries in the Penn World Table that are not at the productivity frontier (as defined above), using GDP data to estimate relative wages, the estimated gain is $10,135, relative to an average income of $9,079, so the gain is 112%. These are of course just rough estimates, relying on a number of strong simplifying assumptions. But unless these assumptions are extremely far off the mark, the results indicate that the gains from open borders would be enormous.

In other words, open borders could double the income of the world’s most disadvantaged people. Far from causing a “brain drain” effect, harming poor countries by poaching productive people, even nonmigrants would benefit from open borders. Furthermore:

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.

How does Kennan arrive at this conclusion? Via a theoretical model, calibrated to fit certain real world data. The approach is oversimplified and crude, yet at the same time, in some ways, painstakingly subtle… but that’s economic theory for you. The logic must be impeccable, but economists’ tolerance for departures from realism can be opaque at first, then, once understood, rather shocking. But one has to do it. A question like “what would happen if the world opened its borders?” involves such a large departure from current reality that common sense and experience fail us. Theory can, so to speak, see in the dark. It allows us to keep thinking clearly, at least, about very remote situations. But down to business.

After a short intro, Kennan’s first really substantive paragraph is:

Before proceeding to analyze a world economy with open borders, the first question that must be answered is whether restrictions on factor mobility have any real effects. If product prices are the same across countries (because there is free trade and transportation is not costly, for example), and if there are two goods that are produced in two different countries, and if the production technologies (for these two goods) are the same across the two countries, then the factor price equalization theorem applies. That is, real wages and other factor prices are equalized across countries even though factors are immobile, because differences in factor prices are implicitly arbitraged through the product market. The theoretical argument is beautiful, but of course the facts are otherwise. For example, wages in the U.S. are about 2.5 times the Mexican wage, for comparable workers.

This will require some unpacking, especially “factor price equalization” and “differences in factor prices are implicitly arbitraged through the product market.” An important result in international economics is that in the “long run,” given certain fairly standard (albeit apparently unrealistic) assumptions, immigration will not reduce wages in the host country, because the mix of industries in the host country will shift to accommodate the new supply of workers to such an extent that wages will be exactly the same. (See the closely related Rybczynski theorem.) Thus, to use the example from the Feenstra and Taylor textbook that I teach this stuff out of, suppose there are two industries, computers and shoes. Computers are a capital-intensive industry, shoes a labor-intensive industry. If a lot of immigrants enter a country called, say, Home, then Home will start producing more shoes and fewer computers.

Fewer computers? Yes, fewer. Even though there are more workers? Not just proportionally fewer? No, fewer in absolute terms. Think of it this way. There’s the same amount of capital in Home as there was before. But there are now more workers. It’s not surprising that the shoe industry will take the lead in absorbing these workers, since its technology is the more labor-intensive of the two. But as it does so, it will lower the marginal product of labor and raise the marginal product of capital in the shoe industry. Or to try to express it without the jargon, the shoe industry will have trouble finding useful things for so many new workers to do without new machines, structures, and other capital goods for them to work with. Even if the shoe industry can’t increase its capital at all, it could find something for all the new workers to do. It will be able to make more shoes. But not that many more shoes. The greater supply of workers increases the shoe industry’s demand for capital. In fact, it implies that the shoe industry wants capital more, at the margin, than the computer industry does. As capital moves from the computer industry to the shoe industry, workers move too, since the scarcity of machines makes them less productive in computers. Importantly, the relative price of computers and shoes stays the same. This is because prices are pinned down by international trade: any deviation in the relative price would cause arbitrage. Wages don’t fall– again, this is in the long run– because relative prices don’t fall, and wages depend on relative prices. The growth of the shoe industry and the shrinkage of the computer industry raise the economy’s demand for labor relative to capital, exactly canceling out the tendency for a greater supply of labor to reduce its wage. This implies not only that wages shouldn’t be reduced by immigration, but also that wages should be the same in every country. Continue reading “John Kennan’s “Open Borders”” »