Year: 2013

The World Bank just announced a new initiative (the Africa Gender Innovation Lab) to support innovative ideas to promote gender equality. I like this idea a lot – as I’ve pointed out before, a lot of ideas about the role of gender inequities in developing Africa, and what to do about them, are pretty uninformed and old-fashioned. Identifying where the key problems really lie, and what to do about them, is key if we’re going to make actual progress on gender relations, just like every social issue.

Markus Goldstein’s post announcing the initiative also alludes one reason why everyone – even sexists – should support gender equality in Africa. A lot of research has found that female farmers have lower crop yields than men. One could imagine a situation in which this is an efficient  outcome: maybe there are increasing returns to labor over the relevant range of effort, and there’s some reason women can’t put in as many hours (e.g. they are forced to spend more time on childcare). This would still be a very unjust outcome, but at least it wouldn’t be wasteful. And I don’t think this story is my unique, hypothetical invention – variants underpin the back-slapping attitude among the privileged in societies around the world: “things are unfair but that’s what makes the world go round.”

The problem with this argument is that there’s no evidence that’s what’s really going on. Chris Udry’s classic paper on gender and agricultural production studies an area in Burkina Faso where men and women from the same household control separate plots of land. Women’s land is less productive, but labor and in particular fertilizer use are heavily concentrated on male-owned land. Households could get 6% boost to total crop production by evening things out. The main reason this happens is because men control the use of fertilizer and don’t share it with their wives. In a counterfactual world where women had more bargaining power, we’d expect to see not just more equity but more total production: sexism is inefficient.

Moreover, this result is very general – it derives not from some special aspect of agriculture in Burkina Faso but from the law of diminishing returns. If a society allocates inputs based on arbitrary, discriminatory rules, this will in general lead to not just unfairness but worse economic outcomes. Suppose our education system funded schools in a way that was driven by race, and favored whites.* $1000 in education spending in a white neighborhood where most kids finish high school doesn’t go nearly as far as $1000 spent in a poor black neighborhood with a high dropout rate. Over the long run, such a policy will reduce economic growth and hurt society as a whole.

*Say, hypothetically, that much of the funding came from local property taxes, that school assignments are based on geography, and that people self-sort into racially-segregated neighborhoods. You know, as a thought experiment.

For an economist, I put relatively little time or effort into sophisticated, mathematical theory, but that still makes me a fairly high outlier in the development and public health research communities. The stock in trade of an economist is the use of mathematical models of behavior that involve agents maximizing utility. These days, with economics having long since left behind its origins as the pure study of markets, this approach to modeling rational decisionmaking is one of the few things that unites the field as a whole.

Sometimes the effort seems a bit silly. It’s a favorite graduate student cocktail party wheeze to suggest that those ivory tower economists have failed miserably, because their models don’t account for (irrationality, free will, psychology, power dynamics, etc.) and hence are useless. I think that reasoning is misguided in a lot of ways, which I won’t get into here, but there’s a deeper problem: what exactly is the point of all that math? Couldn’t we do all of this better as prose? The snide response is to look at discussions of Keynes’s General Theory or the works of Karl Marx: instead of making any progress toward establishing actual scientific facts, academics spent their time arguing about what some particular Great Sage really meant.

A deeper analysis, argued eloquently in an essay by Paul Krugman about the sad history of theory in development economics, is that math forces us to be precise about exactly what we mean. It also helps lead our logic toward conclusions that might not be obvious while keeping us from ending up at apparently-obvious conclusions that don’t follow from our premises. And, he claims, model-making is the not just the only way to be successful in developing scientific theories, but the only way to even try to theorize:

There are many intelligent writers on economics who are able to convince themselves — and sometimes large numbers of other people as well — that they have found a way to transcend the narrowing effect of model-building. Invariably they are fooling themselves. If you look at the writing of anyone who claims to be able to write about social issues without stooping to  restrictive modeling, you will find that his insights are based essentially on the use of metaphor. And metaphor is, of course, a kind of heuristic modeling technique.

The entirety of his essay, The Fall and Rise of Development Economics (written way back in 1994 – this is economist-era Krugman, not editorialist-era Krugman), is readable and interesting. Even mathematically-discinclined readers will be able to understand the simple model he uses as an example (to formalize the Rosenstein-Rodan Big Push theory of development) without too much trouble. Highly recommended.

The public school systems in both Malawi and Uganda (the two countries where I recently spent time doing fieldwork) revolve around a set of massively-important exams that determine whether you get to move on from one level of education to another, and often eligibility for jobs as well. One of the people I was working with in Uganda described primary school there as spending seven years studying for a single test.

It’s hard to overstate the importance of these tests. Uganda’s first such exam is the Primary Leaving Examination, or PLE, which you take after Primary 7 (roughly equivalent to 6th grade as there is no kindergarten). A more-or-less universal practice in the schools I visited in Northern Uganda was to kick out all the poorly-performing P6 pupils before the beginning of P7, leaving just a core of all-stars who spend the year prepping for the test. I’m guessing this is done, in large part, to optimize how good the school looks relative to its competition.

Pressure is high on the pupils as well – it’s common for the names of top performers to be published in newspapers (and hence, by process of elimination, everyone knows who did badly as well). An op-ed I read while in Lira – which I wish I’d cut out and kept, as I can’t find it online – pointed out that this pressure has a cost, and proposed a neat experiment that could be carried out on a grand scale. It’s clear that pupils and their families enjoy the immediate fame of having their names show up in the paper, the author said, but how do they fare down the road? The author proposed that someone should follow up to see how many newspaper-famous PLE success stories end up making it through secondary school.

What’s interesting about this idea is that we could, conceivably, not only do a raw comparison, but actually isolate the causal effect of passing the PLE versus failing it (or of getting a higher grade versus a lower one). The idea is that these exams have hard score cutoffs for passing (or getting a certain grade) and if administered honestly, students can’t control their exact score. Consider a group of exam-takers who are all basically right at the cutoff. Idiosyncratic events on the day of the exam, or random errors, will push them above or below the passing mark. Hence if you look just at that group, you effectively have random assignment to the “pass, name in the paper, life of success and riches” condition or the “fail, no newspaper fame, everybody feels bad for you” condition. You can see how much passing the exam impacts, for example, your wages later in life or the number of kids you have or how many years of school you eventually finish. This approach is called a “regression discontinuity” or “RD” design, and it’s pretty hot in education research these days.

The cool thing about doing this in Malawi or Uganda is that it’s not just a particular school or program – you could study the impact of passing an exam that basically everyone in the country takes. But you’d need the exam scores, plus followup data with a random subset (or all) of the pupils in the country. I can think of ways to do this, but none of them are feasible – unless, to pick one example, some folks at UNEB and the Ugandan Census want to let me at their raw, identifiable data.

Aine McCarthy has a beautifully-written tale of trying to free her car from a river in Tanzania, as a storm moves in:

So, we get out of the truck and start to push. This includes me, Loi (field assistant, driver, friend), two distributors with babies on back, and the family planning training facilitator, who is a nut. A handful of Witamhiya residents are standing around at the riverbank watching us, washing, watching us, watching their cattle. So we ask someone to go get village leader. They send the traditional healer. He is pretty useless. His friend, however, gets two oxen to pull the truck and one more strong man. We try to push while the oxen pull (literally attached to the tow of the front of the truck). Oxen=Tanzanian AAA? Not exactly. It still doesn’t budge and the front tire is getting deeper into the sand.

Also, there is a lot of cow poop. We are basically standing around in a warm poop-green river.  They send for two more oxen. We sit around the river talking about Obama. Four oxen pulling and eight people pushing does nothing for the truck. No cell service in Witamhiya. More sitting around and looking at the oxen. By now, it is 6pm and as if on cue, a dark cloud appears upstream. Huge and growing. The sun is setting and the awesome yet ominous wind that smell of rain starts to blow in our direction.

The whole thing is great, and will ring true to anyone who has tried to navigate crappy developing-country roads in the face of imminent rain. It joins The Economist’s classic tale of a Guiness delivery truck in Cameroon, “The Road to Hell is Unpaved”, as one of my favorite articles about infrastructure in Africa.

It used to be that if you ran an internet scam, the game was to lure people in with the possibility of gaining a small fortune. Now scammers are appealing to our moral compasses to make money. Case in point: I got a very confusing email recently, and following the lead of social science blogging super-hero Andrew Gelman, I’m posting a redacted version here.

Hi Jason,

My name is [name removed] and I came across nonparibus.wordpress.com after searching for people that have referenced or mentioned climate change and global warming. I am part of a team of designers and researchers that put together an infographic showing how bad climate change has gotten and how it’s contributing to the destruction of our planet. I thought you might be interested, so I wanted to reach out.

If this is the correct email and you’re interested in using our content, I’d be happy to share it with you. 🙂

Thank you,

[name removed]

I think this is some kind of meta-blogspam: get me to post their infographic, then include Amazon referral links or something to make money.

There’s almost zero chance this is legitimate or sincere. My only post that mentions climate change is one pointing out that it’s overstated as a cause of fluctuations in rainfall in Malawi and that that is probably be a bad thing. However, if the probably-a-scambot climate change activist reader who emailed me wants to explain why this isn’t bogus, I’m all ears.

Chris Blattman has another post – his most pointed and strongest yet – telling people to get out of field experiments because the market is crowded:

Most field experiments have the hallmarks of a bad field research project. There are four:

1. Takes a long time. Anything requiring a panel survey a year or two apart, or a year of setup time, suffers from this problem.
2. Risky. There are a hundred reasons why any ambitious project may fail, and many do.
3. Expensive. This is driven by any kind of primary data collection, but especially panel or tracking surveys, and especially any Africa or conflict/post-conflict research.
4. High exit costs. This is where experiments excel. If your historical data collection, formal theory, or secondary dataset isn’t working for you, you can put it aside. If your field experiment goes poorly, not only are you stuck with it to the bitter end, but it will take more not less time.

These are all important considerations for any research project, but I was more struck by his aside that he is “suspicious whenever someone puts the method before their question.” Do people running field experiments put the method first? I would argue that they do so less than folks who write (credible) non-experimental social science papers.

The procedure for writing a paper based on a field experiment is 1) think of something you’d like to study and 2) try to come up with an experiment that lets you study it. What about non-experimental papers? Academic lore holds that the current process for grad students writing in economics is 1) sit in a room for four years trying to think of a natural experiment* that happened somewhere and 2) write a paper about whatever that natural experiment is. This is why, for example, we know a lot about the financial returns to education for students who would drop out of school if not for rules that force them to stay until age 17, or the benefits of getting a GED for someone who barely passes the necessary exam.

Let’s take a concrete example: the price elasticity of labor supply. Should we care about the labor supply of cab drivers? Trick question – it doesn’t matter whether taxi driver labor supply is interesting! What’s important is that variations in weather mean that their effective wage changes at random, so we can study their labor supply. That’s where the light is.

In contrast, experiments let us pick our topic and then study it. For example, Jessica Goldberg ran an experiment studying the exact same issue (how labor supply responds to changes in wages) but with a representative sample of Malawians, doing the most common kind of paid work in the country (informal agricultural labor). This kind of work is also common in much of sub-Saharan Africa. Her method – a field experiment – let her pick the topic of her research, and as a result what she studied is the most important category of labor across a wide region.

I’m not saying that Camerer et al.’s cab driver paper isn’t good research, or even that Goldberg’s paper is better. My claim is much simpler, and very hard to dispute: the former paper’s topic was much more driven by its method (finding a useful instrument) than was the latter’s by its method of setting up a targeted experiment.

There are exceptions to this pattern – sometimes a government agency or an NGO has an experiment they want to run that falls into your lap, for example, and some IV-driven research is based on a targeted search. In general, however, it’s misleading to claim that the experimental method often comes before the topic.  That’s a key advantage of running experiments: an RCT lets us choose where to shine the light instead of constantly standing under streetlamps.

I suspect this isn’t what Blattman was driving at – there are topics where observational research is more appropriate (or even the only option, e.g. almost anything in international trade) and we shouldn’t stop studying them just because we can’t do RCTs on them. Nevertheless, the knee-jerk assumption that RCTs are methods-driven rather than topic-driven is pretty common, and, I think, wholly misguided.

I listen to the Freakonomics Radio podcast every week, out of a vague sense of wanting to be on top of how applied microeconomics is seen in the media, and, more important, because I need something to distract my brain as I do all the menial tasks to wrap up my fieldwork here in Malawi; eventually I just run out of other podcasts that interest me. The show is usually a slightly-less-interesting version of This American Life, rather than a real show about microeconomics, which is too bad; I think the world really needs a microeconomics podcast and I wish this one were it but it isn’t, quite. What really bothers me is their pattern of failing to talk about the interesting economics of an issue – there was one short on whether selling beer at sports venues could reduce public drunkenness, which it appears to have done in some cases, but no real explanation of why that may have happened.*

I’ve never been more frustrated with how shallow their coverage is than this week, when they spent the whole episode plugging Freakonomics Experiments, a website that helps you make decisions. The idea is that if you can’t choose whether to, say, change jobs, then you go to the site, take a survey, and then it flips a coin (presumably using a computerized pseudorandom number generator) for you to tell you which option to pick. The heart of the episode is focused on the claimed psychological benefits of flipping a coin to make decisions, and in particular on how it may be preferable to have someone else do the coin flip. I’m not convinced that the Freakonomics team actually believes that claim, but even if they do it’s not at all why they are running this website. They talk very little about the real reason, and that’s unfortunate: unlike hearing people talk about how flipping coins to make choices has improved their lives, the real reason for Freakonomics Experiments is actually interesting, and actually has something to do with economics.

The truth, which everyone has already guessed from the title, is that they are running an experiment. The interesting part is why this is necessary. Take the example of changing jobs. Suppose we want to know what the effect of changing jobs is on your income ten years down the road. We’re trying to estimate b in the equation Y = bC + e, where Y is your eventual income, C is an indicator for whether you changed jobs, and e is an error term. b tells us how much your income goes up if you change jobs versus the case where you stay in the same one. We can’t just compare people who did change jobs to people who did not, because C is not assigned at random. Indeed, headhunters are much more likely to swoop in and hire away people who are going to be worth more in the future, and hence earn more irrespective of where they work. The “coin flip” solves this problem. People who use the site aren’t sure what they want to do, and the random number generator tells them what to do. Now C is assigned at random and we can really measure what happens when you change jobs.

This is all very clever. It’s even more clever than it appears: even if people don’t always obey the random number generator, it is still a valid instrumental variable for the choice of whether to change jobs. That is, we can focus on the variation in C that is driven by the Freakonomics Experiments website – to speak very imprecisely, we can look just at those who do what the “coin” says to do – and look at the effects on that group. What disappoints me is the huge missed opportunity here to talk about the difficulties of doing research on economics (and decisionmaking more broadly) and to help the show’s listeners learn about what kinds of before-and-after comparisons are untrustworthy and why. Going with the cute story, instead of talking about the real reasons for the project, does their audience a disservice.

*I can think of several – common practice at Michigan football games, for example, is to get as drunk as possible before the game so you can stay buzzed for the whole game (And by “you” I of course mean undergrads, since we responsible adults would never do such things). This is an interesting example of the substitution effect: beer at home is a very close substitute for beer at the game. Interestingly the timing and volume of consumption have a big effect on how close those two goods are, which is something that I’ve not seen elsewhere.

This fascinating piece from the Smithsonian Magazine discusses the re-discovery after 40 years of a family that had lived in total isolation in Siberia, having fled the anti-religious Bolsheviks. There’s much to love about this crazy story, which has shades of Hiroo Onoda, the Japanese soldier who refused to surrender until World War II had been over for nearly three decades.

As a development economist, I love how it skewers the still-disturbingly-popular narrative of how subsistence farming is a happy, care-free existence. Deprived of the risk-sharing that even very rural modern economies now have, the Lykovs lost their mother in a famine. Without specialization and trade, all of their possessions fall apart and they end up hunting in the Siberian winter without shoes. Going off the grid and living off the land, as it turns out, is pretty awful.

Even more delightful is something the article doesn’t address directly. The Lykovs fled because of religious persecution, but also because of a broader rejection of modernity and change. They went to the woods to adhere to their timeless traditions of Old Believer Christianity and simple potato farming. Potatoes, indeed, are the lifeblood of their simple, autarkic economy. By the time they were rediscovered, potatoes were virtually all they ate and they even used the peels to make the floor of their hut.

Potatoes are certainly an important aspect of Russian culture – Russia production comes in third in the world – but they are far from timeless. They are a New World crop, and hence their consumption outside the Americas dates back only a few hundred years. This is a pattern I’ve happened across over and over as I’ve interacted with different cultures around the world: many valued traditions have much shorter histories than the people practicing them imagine. This is exemplified by food. Maize (corn), for example, is absolutely central to Malawian culture – it’s far and away the dominant component of people’s diets, and people grow it in literally any patch of open dirt they can find. Here’s a small corn-growing operation that I spotted between two clinics and a church in downtown Zomba:

This is hard to square with the fact that people only corn in this region in the late 1800s. Other cases abound: capsicum peppers in Indian food and tomatoes in Italian food are two items from the list of New World produce that plays a key role in the traditional foods of Old World societies.

A lot of development work comes down to changing the local culture, and some people object to that in principle. The big shifts in what people have traditionally eaten highlight the fact the culture changes all the time, and more rapidly than we might imagine. They make me a lot more comfortable with the idea of targeted attempts to change aspects of a local culture to improve society as a whole.

I’ve spent the past few weeks engaged in the delightful task of data cleaning, which means poring over the thousands of data points my staff collected to spot potential problems. Obsessively browsing my data for errors has reminded me of one of my favorite aspects of Chichewa, which is shared by the other Bantu languages I’ve encountered: Chichewa has neither pronouns nor gendered nouns. This is reflected in how native Chichewa speakers translate phrases to English – unless they are very experienced with our pronoun system, or have a bunch of time to think about it, they tend to pick “she” or “he” as the pronoun to refer to a person roughly at random. So I have notes on my data like “The children say their mother has gone to the market, he sells tomatoes there.”

While this is a bit amusing, I’m not bringing it up to mock these kinds of mistakes. First off, I don’t speak any language as well as my enumerators speak English (maybe Spanish a while back, but I’m way out of practice). Second, I never corrected these issues even out in the field, because I could always tell what they meant, and more importantly because I don’t think the generally-accepted English system of attempting to put force a gender onto all pronouns referring to people is a good one. I’m a big advocate of the singular (or indeterminate-number) they, which was used by Shakespeare but was stolen from us regular folk by the plague of grammatical prescriptivists who have seized control of our language.

The question of gender equality and women’s rights in Africa is a pretty contentious one. I’ve previously highlihted one specific aspect of Malawian culture that is probably more pro-women than the American equivalent, and much more knowledgable people than myself have made a broader case that the importance of gender inequality in commonly-highlighted areas is overblown. Sociologist Susan Watkins makes this case with regard to AIDS in an excellent book chapter called “Back to Basics” which I cannot find online. In joint work with Michelle Poulin, Watkins argues that an over-focus on women is actually hurting them by failing to target the key drivers of the HIV epidemic. Conversely, certain aspects of women’s disempowerment in Africa are undeniable, such as their relatively rarity in the upper levels of government (although America is still not much better).

This, though, is a very straightforward advantage of the language that most people are raised speaking in Malawi. In English, many sentences are subtle power struggles. Do we default to “he” to refer to people of unspecified gender? Do we force a switch to “she”, or try for a hybrid “he/she” or “she/he”? Switching the default to “she” implicitly acknowledges that the default person is male, and over the long term it’s just as unfair as “he”. “They”, my own preference, still leaves me subconsciously assuming a male. Indeed, even when I’m given no pronouns or references to gender at all, I still automatically assume people are male. Not only are there no girls on the internet, but when I was frustrated by the high error rate of one of my data enterers, I found myself growing to hate “him” and “his” laziness (as it turns out the person was indeed male). There are probably many reasons for this, but I attribute it largely to the fact that I am forced, even mentally, to use a gendered pronoun. Chichewa places no such strictures on its speakers. The fact that a generic person does not have to have a gender (which would most likly end up being male) is a small advantage to women in Malawi, and one America would do well to emulate.

*Lest you think this latter aspect makes the language easier to learn, instead of genders Chichewa nouns fall into one of 11 different categories that govern the prefixes on associated adjectives and verbs. This means that even when I can make myself understood, I’m constantly embarassing myself with grammatical mistakes as egregious as saying “Me like a apples”.

The solution to America’s burgeoning entitlement crisis is not benefit cuts, nor abolishing social welfare programs, but immigration. It is time for politicians to be bold and take a stand on this.

Like many fiscally-conservative outlets, the Economist has not slowed down in its warnings about America’s long-run fiscal challenges. We have a bunch of unfunded entitlements, the claim goes, and what we need to do is cut benefits in order to solve the problem. And all the haranguing over the Fiscal Cliff and the Debt Ceiling is doing nothing to address the underlying fiscal imbalances. Medicare and Social Security benefits (that is, total outlays on these programs) must be cut!, they claim.

There’s something to this line of reasoning, but we all need to be a lot more honest about why these fiscal imbalances exist. The gap between inflows into these systems comes from two sources. One is the rising per-unit cost of healthcare. The steady upward march of healthcare prices has slowed somewhat, but still drastically outpaces inflation. The other is the declining “worker-to-beneficiary ratio”: the number of people paying into Medicare and Social Security is declining over time, while the number of people getting benefits is rising.

Conservatives like to carp about Obamacare not doing enough about healthcare costs, but neither party has made any serious proposals to do anything about these cost rises. Healthcare is an overly-complicated muddle in which no one knows how much anything really costs and there is little competition on either side of the market. I could write a whole book about the subject, and only know about small parts of it. Before I started my Ph.D. my job at Tom MaCurdy’s research firm was focused on one particular issue, which is that doctors and health care organizations are a lot like mechanics: they both tell you what services you need and sell you those services. This is one factor leading to excessive treatment and testing, which drives up costs, but there are many more.

Fixing the problem of healthcare prices will take a long time if it is possible at all, and has little to do with Medicare per se. Prices are rocketing upward in the private sector as well, and most private-sector payment policies are equally as stupid as what government programs do. Clearly we cannot focus on health care if we want to have a chance of doing anything about entitlement reform in the near term.

What about the beneficiary ratio? Can’t we fix that, by raising the age at which people are benefit-eligible? I definitely think raising the retirement age is a good idea: Sam King and I laid out the case for this a few years ago. Raising the eligibilty age for these programs will do little, however, and following the George W. Bush individual accounts plan would probably not do anything at all.

The reason is that as long as people retire at age 65, they will need to fund that retirement somehow. That funding can only come from claims on the income of current workers. If people have individual retirement accounts, they will hold investments that they can cash in through various means, but they would always need to grab some of current workers’ incomes, e.g. by selling stocks to them. No matter what mechanism we use to fund retirements, we will still have a worker-beneficiary ratio problem if people continue to retire at 65. This isn’t my idea – Ron Lee of UC Berkeley and Andrew Mason of the University of Hawaii have written an excellent book on the subject, available for free here. The graphs are awesome.

If we raise the Medicare and Social Security eligibility age, we will do a little to help abate this issue, especially if this induces a norm of a higher retirement age. Given how healthy many 65-year-olds are nowadays, this is sensible, as are programs to help older workers of any age who cannot work. Changing norms takes a long time, however, and we have a burgeoning problem already.

We have a solution to this problem, and it’s already being debated elsewhere in the halls of Congress: immigration reform. In a heartening turn of events, a number of Republicans are advocating letting America’s millions of illegal migrants stay in the country legally, and making legal immigration more streamlined. Where people are still failing, however, is in linking immigration reform to our fiscal challenges. Letting in more immigrants is the one thing rich countries can do to increase the number of workers per retireee. Not only that, but naturalized citizens have more children than native-born Americans, further alleviating our long-term problem. Loosening immigration restrictions would buy is decades of much-needed breathing space to start edging up the retirement age.

Far from being a selfish move, this would have massive benefits for both migrants and their home countries. Michael Clemens has made a passionate moral case for more immigration – here he is on Development Drums. Immigrants to the US see a huge spike in earnings, much of which they send back home to help their families. Many eventually return home, bringing wealth and skills to their communities. In attempting to gain skills that will be valuable abroad, people who want to migrate get more education and training, so even the ones who don’t make the cut end up richer (and bring benefits to their communities). For example, a large number of Filipinos become nurses in order to work abroad; many fail to find positions overseas, contributing to the country’s relatively high-quality healthcare.

Finally, this is simply the right thing to do. The world’s current national borders were largely determined through imperial conquest and deal-making by current rich-world countries. They have no special status, and it’s hard to see a moral case for caring more about people who lived on one side of an arbitrary line on a map than another.

America is on the verge of something wonderful here. I am the great-grandson of European emigrants who settled in America. My Irish and Italian forebears were the wrong kind of immigrants. They were different from the good kind, who had come earlier. They didn’t assimilate. They were genetically inferior, and not as smart as people from England or Germany. They stole our jobs and destroyed our way of life. Until they didn’t – until we realized that like all naturalized citizens, they were the proudest and most loyal Americans of all. Our culture has always cycled between the open borders that characterized the country originally, and periods of xenophobia and racism in which we have tried to keep foreigners out. It is time to get back to our roots. In so doing, we will also address the largest long-run economic problem we face.