Most trade barriers are not tariffs

Jul 8 JDN 2458309

When we talk about “protectionism” or “trade barriers”, what usually comes to mind is tariffs: taxes imposed on imports or exports. But especially now that international trade organizations have successfully reduced tariffs around the world, most trade barriers are not of this form at all.

Especially in highly-developed countries, but really almost everywhere, the most common trade barriers are what is simply but inelegantly called non-tariff barriers to trade: this includes licenses, quotas, subsidies, bailout guarantees, labeling requirements, and even some environmental regulations.

Non-tariff barriers are much more complicated to deal with, for at least three reasons.

First, with the exception of quotas and subsidies, non-tariff barriers are not easily quantifiable. We can easily put a number on the value of a tariff (though its impact is somewhat subtler than that), but this is not so easy for the effect of a bailout guarantee or a labeling requirement.

Second, non-tariff barriers are often much harder to detect. It’s obvious enough that imposing a tax on imported steel will reduce our imports of steel; but it requires a deeper understanding of the trade system to understand why bailing out domestic banks would distort financial flows, interest rates and exchange rates (even though the impact of this may actually be larger—the effect on global trade of US bank bailouts was between $35 billion and $110 billion).

Third, some trade barriers are either justifiable or simply inevitable. Simply having customs screening at the border is a non-tariff barrier, but it is widely regarded as a justifiable security measure (and I agree, by the way, even though I am generally in favor of much more open borders). Requiring strict labor and environmental standards on the production of products both domestic and imported is highly beneficial, but also imposes a trade barrier. In a broader sense, differences in language and culture could even be regarded as trade barriers (they certainly increase the real cost of trade), but it’s not clear that we could eliminate such things even if we wanted to.

This requires us to look very closely at almost every major government policy, to see how it might be distorting world trade. Some policies won’t meaningfully distort trade at all; these are not trade barriers. Others will distort trade, but are beneficial enough in other ways that they are still worth it; these are justifiable trade barriers. Still others will distort trade so much that they cannot be justified despite their other benefits. Finally, some policies will be put in place more or less explicitly to distort trade, usually in the form of protectionism to prop up domestic industries.

Protectionist policies are of course the first things to get rid of. Honestly, it baffles me that people even want to impose them in the first place. For some reason they think of exports as the benefit and imports as the cost, when it’s really the other way around; when we impose protectionism, we go out of our way to make it harder to get cars and iPhones so that we can stop other countries from taking our green paper. This seems to be tied to the fact that people think of jobs as something desirable, when really it’s wealth that’s desirable, and jobs are just one way of getting wealth—in some sense the most expensive way. Our macroeconomic policy obsesses over inflation, which is almost literally meaningless (as long as it is not too unpredictable, really nothing would change if inflation were raised from 2% to 4% or even 10%) and unemployment, which is at best an imperfect indicator of what we really should care about, namely the welfare of our people. A world of full employment with poverty wages is much worse than a world of high unemployment where a basic income provides for everyone’s needs. It is true that in our current system, unemployment is closely tied to a lot of very bad outcomes—but I maintain that this is largely because unemployment entails losing your income and your healthcare.

Some regulations that appear benign may actually be harmful because of their effects on trade. Yet I should also point out that it’s possible to go too far the other direction, and start tearing down all regulations in the name of reducing trade barriers. We particularly seem to do this in the financial industry, where “deregulation” seems to be on everyone’s lips until it causes a crisis, then we impose some regulations that fix the worst problems, things look good for awhile—and then we go back around and everyone starts talking about “deregulation” again. Meanwhile, the same people who talk about “freedom” as an excuse for removing financial safeguards are the ones who lock up children at the border. I think this is something that needs to be reframed: Which regulations are you removing? Just what, exactly, are you making legal that wasn’t before? Legalizing murder would be “deregulation”.

Trade policy, therefore, is a very delicate balance, between removing distortions and protecting legitimate public interests, between the needs of your own country and the world as a whole. This is why we need this whole apparatus of international trade institutions; it’s not a simple matter.

But I will say this: It would probably help if people educated themselves a bit more about how trade actually works before voting in politicians who promise to “save their jobs” from foreign competition.

Forget the Doughnut. Meet the Wedge.

Mar 11 JDN 2458189

I just finished reading Kate Raworth’s book Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist; Raworth also has a whole website dedicated to the concept of the Doughnut as a way of rethinking economics.

The book is very easy to read, and manages to be open to a wide audience with only basic economics knowledge without feeling patronizing or condescending. Most of the core ideas are fundamentally sound, though Raworth has a way of making it sound like she is being revolutionary even when most mainstream economists already agree with the core ideas.

For example, she makes it sound like it is some sort of dogma among neoclassical economists that GDP growth must continue at the same pace forever. As I discussed in an earlier post, the idea that growth will slow down is not radical in economics—it is basically taken for granted in the standard neoclassical growth models.

Even the core concept of the Doughnut isn’t all that radical. It’s based on the recognition that economic development is necessary to end poverty, but resources are not unlimited. Then combine that with two key assumptions: GDP growth requires growth in energy consumption, and growth in energy consumption requires increased carbon emissions. Then, the goal should be to stay within a certain range: We want to be high enough to not have poverty, but low enough to not exceed our carbon budget.

Why a doughnut? That’s… actually a really good question. The concept Raworth presents is a fundamentally one-dimensional object; there’s no reason for it to be doughnut-shaped. She could just as well have drawn it on a single continuum, with poverty at one end, unsustainability at the other end, and a sweet spot in the middle. The doughnut shape adds some visual appeal, but no real information.

But the fundamental assumptions that GDP requires energy and energy requires carbon emissions are simply false—especially the second one. Always keep one thing in mind whenever you’re reading something by environmentalists telling you we need to reduce economic output to save the Earth: Nuclear power does not produce carbon emissions.

This is how the environmentalist movement has shot itself—and the world—in the foot for the last 50 years. They continually refuse to admit that nuclear power is the best hope we have for achieving both economic development and ecological sustainability. They have let their political biases cloud their judgment on what is actually best for humanity’s future.

I will give Raworth some credit for not buying into the pipe dream that we can somehow transition rapidly to an entirely solar and wind-based power grid—renewables only produce 6% of world energy (the most they ever have), while nuclear produces 10%. And nuclear power certainly has its downsides, particularly in its high cost of construction. It may in fact be the case that we need to reduce economic output somewhat, particularly in the very richest countries, and if so, we need to find a way to do that without causing social and political collapse.

The Dougnut is a one-dimensional object glorified by a two-dimensional diagram.

So let me present you with an actual two-dimensional object, which I call the Wedge.

On this graph, the orange dots plot actual GDP per capita (at purchasing power parity) on the X axis against actual CO2 emissions per capita on the Y-axis. The green horizonal line is a CO2 emission target of 3 tonnes per person per year based on reports from the International Panel on Climate Change.

Wedge_full

As you can see, most countries are above the green line. That’s bad. We need the whole world below that green line. The countries that are below the line are largely poor countries, with a handful of middle-income countries mixed in.

But it’s the blue diagonal line that really makes this graph significant, what makes it the Wedge. That line uses Switzerland’s level of efficiency to estimate a frontier of what’s possible. Switzerland’s ratio of GDP to CO2 is the best in the world, among countries where the data actually looks reliable. A handful of other countries do better in the data, but for some (Macau) it’s obviously due to poor counting of indirect emissions and for others (Rwanda, Chad, Burundi) we just don’t have good data at all. I think Switzerland’s efficiency level of $12,000 per ton of CO2 is about as good as can be reasonably expected for most countries over the long run.

Our goal should be to move as far right on the graph as we can (toward higher levels of economic development), but always staying inside this Wedge: Above the green line, our CO2 emissions are too high. Below the blue line may not be technologically feasible (though of course it’s worth a try). We want to aim for the point of the wedge, where GDP is as high as possible but emissions are still below safe targets.

Zooming in on the graph gives a better view of the Wedge.

Wedge_zoomed

The point of the Wedge is about $38,000 per person per year. This is not as rich as the US, but it’s definitely within the range of highly-developed countries. This is about the same standard of living as Italy, Spain, or South Korea. In fact, all three of these countries exceed their targets; the closest I was able to find to a country actually hitting the point of the wedge was Latvia, at $27,300 and 3.5 tonnes per person per year. Uruguay also does quite well at $22,400 and 2.2 tonnes per person per year.

Some countries are within the Wedge; a few, like Uruguay, quite close to the point, and many, like Colombia and Bangladesh, that are below and to the left. For these countries, a “stay the course” policy is the way to go: If they keep up what they are doing, they can continue to experience economic growth without exceeding their emission targets.

 

But the most important thing about the graph is not actually the Wedge itself: It’s all the countries outside the Wedge, and where they are outside the Wedge.

There are some countries, like Sweden, France, and Switzerland, that are close to the blue line but still outside the Wedge because they are too far to the right. These are countries for whom “degrowth” policies might actually make sense: They are being as efficient in their use of resources as may be technologically feasible, but are simply producing too much output. They need to find a way to scale back their economies without causing social and political collapse. My suggestion, for what it’s worth, is progressive taxation. In addition to carbon taxes (which are a no-brainer), make income taxes so high that they start actually reducing GDP, and do so without fear, since that’s part of the point; then redistribute all the income as evenly as possible so that lower total income comes with much lower inequality and the eradication of poverty. Most of the country will then be no worse off than they were, so social and political unrest seems unlikely. Call it “socialism” if you like, but I’m not suggesting collectivization of industry or the uprising of the proletariat; I just want everyone to adopt the income tax rates the US had in the 1950s.

But most countries are not even close to the blue line; they are well above it. In all these countries, the goal should not be to reduce economic output, but to increase the carbon efficiency of that output. Increased efficiency has no downside (other than the transition cost to implement it): It makes you better off ecologically without making you worse off economically. Bahrain has about the same GDP per capita as Sweden but produces over five times the per-capita carbon emissions. Simply by copying Sweden they could reduce their emissions by almost 19 tonnes per person per year, which is more than the per-capita output of the US (and we’re hardly models of efficiency)—at absolutely no cost in GDP.

Then there are countries like Mongolia, which produces only $12,500 in GDP but 14.5 tonnes of CO2 per person per year. Mongolia is far above and to the left of the point of the Wedge, meaning that they could both increase their GDP and decrease their emissions by adopting the model of more efficient countries. Telling these countries that “degrowth” is the answer is beyond perverse—cut Mongolia’s GDP by 2/3 and you would throw them into poverty without even bringing carbon emissions down to target.

We don’t need to overthrow capitalism or even give up on GDP growth in general. We need to focus on carbon, carbon, carbon: All economic policy from this point forward should be made with CO2 reduction in mind. If that means reducing GDP, we may have to accept that; but often it won’t. Switching to nuclear power and public transit would dramatically reduce emissions but need have no harmful effect on economic output—in fact, the large investment required could pull a country out of recession.

Don’t worry about the Doughnut. Aim for the point of the Wedge.

Did the World Bank modify its ratings to manipulate the outcome of an election in Chile?

Jan 21 JDN 2458140

(By the way, my birthday is January 19. I can’t believe I’m turning 30.)

This is a fairly obscure news item, so you may have missed it. It should be bigger news than it is.
I can’t fault the New York Times for having its front page focus mainly on the false missile alert that was issued to some people in Hawaii; a false alarm of nuclear attack definitely is the most important thing that could be going on in the world, short of course of actual nuclear war.

CNN, on the other hand, is focused entirely on Trump. When I first wrote this post, they were also focused on Trump, mainly interested in asking whether Trump’s comments about “immigrants from shithole countries” was racist. My answer: Yes, but not because he said the countries were “shitholes”. That was crude, yes, but not altogether inaccurate. Countries like Syria, Afghanistan, and Sudan are, by any objective measure, terrible places. His comments were racist because they attributed that awfulness to the people leaving these countries. But in fact we have a word for immigrants who flee terrible places seeking help and shelter elsewhere: Refugees. We call those people refugees. There are over 10 million refugees in the world today, most of them from Syria.

So anyway, here’s the news item you should have heard about but probably didn’t: The Chief Economist of the World Bank (Paul Romer, who coincidentally I mentioned in my post about DSGE models) has opened an investigation into the possibility that the World Bank’s ratings of economic freedom were intentionally manipulated in order to tilt a Presidential election in Chile.

The worst part is, it may have worked: Chile’s “Doing Business” rating consistently fell under President Michelle Bachelet and rose under President Sebastian Piñera, and Piñera won the most recent election. Was that the reason he won? Who knows? I’m still not entirely clear on how we ended up with President Trump. But it very likely contributed.

The World Bank is supposed to be an impartial institution representing the interests of global economic development. I’m not naive; I recognize that no human institution is perfect, and there will always be competing political and economic interests within any complex institution. Development economists are subject to cognitive biases just like anyone else. If this was the work of a handful of economic analysts (or if Romer turns out to be wrong and the changes in statistical methodology were totally reasonable), so be it; let’s make sure that the bias is corrected and the analysts involved are punished.

But I fear that the rot may run deeper than this. The World Bank is effectively a form of unelected international government. It has been accused of inherent pro-capitalist (or even racist) bias due to the fact that Western governments are overrepresented in its governance, but I actually consider that accusation unfair: There are very good reasons to make sure that your international institutions are managed by liberal democracies, and turns out that most of the world’s liberal democracies are Western. The fact that the US, France, Germany, and the UK make most of the decisions is entirely sensible: Those are in fact the countries we should want making global decisions.

China is not underrepresented, because China is not a democracy and doesn’t deserve to be represented. They are already more represented in the World Bank than they should be, because representing the PRC is not actually representing the interests of the people of China. Russia and Saudi Arabia are undeniably overrepresented. India is underrepresented; they should be complaining. Some African democracies, such as Namibia and Botswana, would also have a legitimate claim to underrepresentation. But I don’t lose any sleep over the fact that Zimbabwe and Iran aren’t getting votes in the World Bank. If and when those countries actually start representing their people, then we can talk about giving them representation in world government. I don’t see how refusing to give international authority to dictators and theocrats constitutes racism or pro-capitalist bias.

That said, there are other reasons to think that the World Bank might actually have some sort of pro-capitalist bias. The World Bank was instrumental in forming the Washington Consensus, which opened free trade and increase economic growth worldwide, but also exposed many poor countries to risk from deregulated financial markets and undermined social safety nets through fiscal austerity programs. They weren’t wrong to want more free trade, and many of their reforms did make sense; but they were at best wildly overconfident in their policy prescriptions, and at worst willing to sacrifice people in poor countries at the altar of bank profits. World poverty has in fact fallen by about half since 1990, and the World Bank has a lot to do with that. But things may have gone faster and smoother if they hadn’t insisted on removing so many financial regulations so quickly without clear forecasts of what would happen. I don’t share Jason Hickel’s pessimistic view that the World Bank’s failures were intentional acts toward an ulterior agenda, but I can see how it begins to look that way when they keep failing the same ways over and over again. (I instead invoke Hanlon’s razor: “Never attribute to malice that which is adequately explained by stupidity.”)

There are also reports of people facing retaliation for criticizing World Bank projects, including those within the World Bank who raise ethical concerns. If this was politically-motivated data manipulation, there may have been people who saw it happening, but were afraid to say anything for fear of being fired or worse.

And Chile in particular has reason to be suspicious. The World Bank suddenly started giving loans to Chile when Augusto Pinochet took power (the CIA denies supporting the coup, by the way—though, given the source, I can understand why one would take that with a grain of salt), and did so under the explicit reasoning that an authoritarian capitalist regime was somehow “more trustworthy” than a democratic socialist regime. Even in the narrow sense of financial creditworthiness that seems difficult to defend; the World Bank knew almost nothing about what kind of government Pinochet was going to create, and in fact despite the so-called “Miracle of Chile”, rapid economic growth in Chile didn’t really happen until the 1990s, after Chile became a democratic capitalist regime.

What I’m really getting at here is that the World Bank has a lot to answer for. I am prepared to believe that most of these actions were honest mistakes or ideological blinders, rather than corruption or cruelty; but even so, when millions of lives are at stake, even honest mistakes aren’t so forgivable. They should be looking for ways to improve their internal governance to make sure that mistakes are caught and corrected quickly. They should be constantly vigilant for biases—either intentional or otherwise—that might seep into their research. Error should be met with immediate correction and public apology; malfeasance should be met with severe punishment.

Perhaps Romer’s investigation actually signals a shift toward such a policy. If so, this is a very good thing. If only we had done this, say, thirty years ago.

What exactly is “gentrification”? How should we deal with it?

Nov 26, JDN 2458083

“Gentrification” is a word that is used in a variety of mutually-inconsistent ways. If you compare the way social scientists use it to the way journalists use it, for example, they are almost completely orthogonal.

The word “gentrification” is meant to invoke the concept of a feudal gentry—a hereditary landed class that extracts rents from the rest of the population while contributing little or nothing themselves.

If indeed that is what we are talking about, then obviously this is bad. Moreover, it’s not an entirely unfounded fear; there are some remarkably strong vestiges of feudalism in the developed world, even in the United States where we never formally had a tradition of feudal titles. There really is a significant portion of the world’s wealth held by a handful of billionaire landowner families.

But usually when people say “gentrification” they mean something much broader. Almost any kind of increase in urban real estate prices gets characterized as “gentrification” by at least somebody, and herein lies the problem.

In fact, the kind of change that is most likely to get characterized as “gentrification” isn’t even the rising real estate prices we should be most worried about. People aren’t concerned when the prices of suburban homes double in 20 years. You might think that things that are already too expensive getting more expensive would be the main concern, but on the contrary, people are most likely to cry “gentrification” when housing prices rise in poor areas where housing is cheap.

One of the most common fears about gentrification is that it will displace local residents. In fact, the best quasi-experimental studies show little or no displacement effect. It’s actually mainly middle-class urbanites who get displaced by rising rents. Poor people typically own their homes, and actually benefit from rising housing prices. Young upwardly-mobile middle-class people move to cities to rent apartments near where they work, and tend to assume that’s how everyone lives, but it’s not. Rising rents in a city are far more likely to push out its grad students than they are poor families that have lived there for generations. Part of why displacement does not occur may be because of policies specifically implemented to fight it, such as subsidized housing and rent control. If that’s so, let’s keep on subsidizing housing (though rent control will always be a bad idea).

Nor is gentrification actually a very widespread phenomenon. The majority of poor neighborhoods remain poor indefinitely. In most studies, only about 30% of neighborhoods classified as “gentrifiable” actually end up “gentrifying”. Less than 10% of the neighborhoods that had high poverty rates in 1970 had low poverty rates in 2010.

Most people think gentrification reduces crime, but in the short run the opposite is the case. Robbery and larceny are higher in gentrifying neighborhoods. Criminals are already there, and suddenly they get much more valuable targets to steal from, so they do.

There is also a general perception that gentrification involves White people pushing Black people out, but this is also an overly simplistic view. First of all, a lot of gentrification is led by upwardly-mobile Black and Latino people. Black people who live in gentrified neighborhoods seem to be better off than Black people who live in non-gentrified neighborhoods; though selection bias may contribute to this effect, it can’t be all that strong, or we’d observe a much stronger displacement effect. Moreover, some studies have found that gentrification actually tends to increase the racial diversity of neighborhoods, and may actually help fight urban self-segregation, though it does also tend to increase racial polarization by forcing racial mixing.

What should we conclude from all this? I think the right conclusion is we are asking the wrong question.

Rising housing prices in poor areas aren’t inherently good or inherently bad, and policies designed specifically to increase or decrease housing prices are likely to have harmful side effects. What we need to be focusing on is not houses or neighborhoods but people. Poverty is definitely a problem, for sure. Therefore we should be fighting poverty, not “gentrification”. Directly transfer wealth from the rich to the poor, and then let the housing market fall where it may.

There is still some role for government in urban planning more generally, regarding things like disaster preparedness, infrastructure development, and transit systems. It may even be worthwhile to design regulations or incentives that directly combat racial segregation at the neighborhood level, for, as the Schelling Segregation Model shows, it doesn’t take a large amount of discriminatory preference to have a large impact on socioeconomic outcomes. But don’t waste effort fighting “gentrification”; directly design policies that will incentivize desegregation.

Rising rent as a proportion of housing prices is still bad, and the fundamental distortions in our mortgage system that prevent people from buying houses are a huge problem. But rising housing prices are most likely to be harmful in rich neighborhoods, where housing is already overpriced; in poor neighborhoods where housing is cheap, rising prices might well be a good thing.
In fact, I have a proposal to rapidly raise homeownership across the United States, which is almost guaranteed to work, directly corrects an enormous distortion in financial markets, and would cost about as much as the mortgage interest deduction (which should probably be eliminated, as most economists agree). Give each US adult a one-time grant voucher which gives them $40,000 that can only be spent as a down payment on purchasing a home. Each time someone turns 18, they get a voucher. You only get one over your lifetime, so use it wisely (otherwise the policy could become extremely expensive); but this is an immediate direct transfer of wealth that also reduces your credit constraint. I know I for one would be house-hunting right now if I were offered such a voucher. The mortgage interest deduction means nothing to me, because I can’t afford a down payment. Where the mortgage interest deduction is regressive, benefiting the rich more than the poor, this policy gives everyone the same amount, like a basic income.

In the short run, this policy would probably be expensive, as we’d have to pay out a large number of vouchers at once; but with our current long-run demographic trends, the amortized cost is basically the same as the mortgage interest deduction. And the US government especially should care about the long-run amortized cost, as it is an institution that has lasted over 200 years without ever missing a payment and can currently borrow at negative real interest rates.

How rich are we, really?

Oct 29, JDN 2458056

The most commonly-used measure of a nation’s wealth is its per-capita GDP, which is simply a total of all spending in a country divided by its population. More recently we adjust for purchasing power, giving us GDP per capita at purchasing power parity (PPP).

By this measure, the United States always does well. At most a dozen countries are above us, most of them by a small amount, and all of them are quite small countries. (For fundamental statistical reasons, we should expect both the highest and lowest average incomes to be in the smallest countries.)

But this is only half the story: It tells us how much income a country has, but not how that income is distributed. We should adjust for inequality.

How can we do this? I have devised a method that uses the marginal utility of wealth plus a measure of inequality called the Gini coefficient to work out an estimate of the average utility, instead of the average income.

I then convert back into a dollar figure. This figure is the income everyone would need to have under perfect equality, in order to give the same real welfare as the current system. That is, if we could redistribute wealth in such a way to raise everyone above this value up to it, and lower everyone above this value down to it, the total welfare of the country would not change. This provides a well-founded ranking of which country’s people are actually better off overall, accounting for both overall income and the distribution of that income.

The estimate is sensitive to the precise form I use for marginal utility, so I’ll show you comparisons for three different cases.

The “conservative” estimate uses a risk aversion parameter of 1, which means that utility is logarithmic in income. The real value of a dollar is inversely proportional to the number of dollars you already have.

The medium estimate uses a risk aversion parameter of 2, which means that the real value of a dollar is inversely proportional to the square of the number of dollars you already have.

And then the “liberal” estimate uses a risk aversion parameter of 3, which means that the real value of a dollar is inversely proportional to the cube of the number of dollars you already have.

I’ll compare ten countries, which I think are broadly representative of classes of countries in the world today.

The United States, the world hegemon which needs no introduction.

China, rising world superpower and world’s most populous country.

India, world’s largest democracy and developing economy with a long way to go.

Norway, as representative of the Scandinavian social democracies.

Germany, as representative of continental Europe.

Russia, as representative of the Soviet Union and the Second World bloc.

Saudi Arabia, as representative of the Middle East petrostates.

Botswana, as representative of African developing economies.

Zimbabwe, as representative of failed Sub-Saharan African states.

Brazil, as representative of Latin American developing economies.
The ordering of these countries by GDP per-capita PPP is probably not too surprising:

  1. Norway 69,249
  2. United States 57,436
  3. Saudi Arabia 55,158
  4. Germany 48,111
  5. Russia 26,490
  6. Botswana 17,042
  7. China 15,399
  8. Brazil 15,242
  9. India 6,616
  10. Zimbabwe 1,970

Norway is clearly the richest, the US, Saudi Arabia, and Germany are quite close, Russia is toward the upper end, Botswana, China, and Brazil are close together in the middle, and then India and especially Zimbabwe are extremely poor.

But now let’s take a look at the inequality in each country, as measured by the Gini coefficient (which ranges from 0, perfect equality, to 1, total inequality).

  1. Botswana 0.605
  2. Zimbabwe 0.501
  3. Brazil 0.484
  4. United States 0.461
  5. Saudi Arabia 0.459
  6. China 0.422
  7. Russia 0.416
  8. India 0.351
  9. Germany 0.301
  10. Norway 0.259

The US remains (alarmingly) close to Saudi Arabia by this measure. Most of the countries are between 40 and 50. But Botswana is astonishingly unequal, while Germany and Norway are much more equal.

With that in mind, let’s take a look at the inequality-adjusted per-capita GDP. First, the conservative estimate, with a parameter of 1:

  1. Norway 58700
  2. United States 42246
  3. Saudi Arabia 40632
  4. Germany 39653
  5. Russia 20488
  6. China 11660
  7. Botswana 11138
  8. Brazil 11015
  9. India 5269
  10. Zimbabwe 1405

So far, ordering of nations is almost the same compared to what we got with just per-capita GDP. But notice how Germany has moved up closer to the US and Botswana actually fallen behind China.

Now let’s try a parameter of 2, which I think is the closest to the truth:

  1. Norway 49758
  2. Germany 32683
  3. United States 31073
  4. Saudi Arabia 29931
  5. Russia 15581
  6. China 8829
  7. Brazil 7961
  8. Botswana 7280
  9. India 4197
  10. Zimbabwe 1002

Now we have seen some movement. Norway remains solidly on top, but Germany has overtaken the United States and Botswana has fallen behind not only China, but also Brazil. Russia remains in the middle, and India and Zimbawbe remain on the bottom.

Finally, let’s try a parameter of 3.

  1. Norway 42179
  2. Germany 26937
  3. United States 22855
  4. Saudi Arabia 22049
  5. Russia 11849
  6. China 6685
  7. Brazil 5753
  8. Botswana 4758
  9. India 3343
  10. Zimbabwe 715

Norway has now pulled far and away ahead of everyone else. Germany is substantially above the United States. China has pulled away from Brazil, and Botswana has fallen almost all the way to the level of India. Zimbabwe, as always, is at the very bottom.

Let’s compare this to another measure of national well-being, the Inequality-Adjusted Human Development Index (which goes from 0, the worst, to 1 the best). This index combines education, public health, and income, and adjusts for inequality. It seems to be a fairly good measure of well-being, but it’s very difficult to compile data for, so a lot of countries are missing (including Saudi Arabia); plus the precise weightings on everything are very ad hoc.

  1. Norway 0.898
  2. Germany 0.859
  3. United States 0.796
  4. Russia 0.725
  5. China 0.543
  6. Brazil 0.531
  7. India 0.435
  8. Botswana 0.433
  9. Zimbabwe 0.371

Other than putting India above Botswana, this ordering is the same as what we get from my (much easier to calculate and theoretically more well-founded) index with either a parameter of 2 or 3.

What’s more, my index can be directly interpreted: The average standard of living in the US is as if everyone were making $31,073 per year. What exactly is an IHDI index of 0.796 supposed to mean? We’re… 79.6% of the way to the best possible country?

In any case, there’s a straightforward (if not terribly surprising) policy implication here: Inequality is a big problem.

In particular, inequality in the US is clearly too high. Despite an overall income that is very high, almost 18 log points higher than Germany, our overall standard of living is actually about 5 log points lower due to our higher level of inequality. While our average income is only 19 log points lower than Norway, our actual standard of living is 47 log points lower.

Inequality in Botswana also means that their recent astonishing economic growth is not quite as impressive as it at first appeared. Many people are being left behind. While in raw income they appear to be 10 log points ahead of China and only 121 log points behind the US, once you adjust for their very high inequality they are 19 log points behind China, and 145 log points behind the US.

Of course, some things don’t change. Norway is still on top, and Zimbabwe is still on the bottom.

When are we going to get serious about climate change?

Oct 8, JDN 24578035

Those two storms weren’t simply natural phenomena. We had a hand in creating them.

The EPA doesn’t want to talk about the connection, and we don’t have enough statistical power to really be certain, but there is by now an overwhelming scientific consensus that global climate change will increase hurricane intensity. The only real question left is whether it is already doing so.

The good news is that global carbon emissions are no longer rising. They have been essentially static for the last few years. The bad news is that this is almost certainly too little, too late.

The US is not on track to hit our 2025 emission target; we will probably exceed it by at least 20%.

But the real problem is that the targets themselves are much too high. Most countries have pledged to drop emissions only about 8-10% below their 1990s levels.

Even with the progress we have made, we are on track to exceed the global carbon budget needed to keep warming below 2 C by the year 2040. We have been reducing emission intensity by about 0.8% per year—we need to be reducing it by at least 3% per year and preferably faster. Highly-developed nations should be switching to nuclear energy as quickly as possible; an equitable global emission target requires us to reduce our emissions by 80% by 2050.

At the current rate of improvement, we will overshoot the 2 C warming target and very likely the 3C target as well.

Why aren’t we doing better? There is of course the Tragedy of the Commons to consider: Each individual country acting in its own self-interest will continue to pollute more, as this is the cheapest and easiest way to maintain industrial development. But then if all countries do so, the result is a disaster for us all.
But this explanation is too simple. We have managed to achieve some international cooperation on this issue. The Kyoto protocol has worked; emissions among Kyoto member nations have been reduced by more than 20% below 1990 levels, far more than originally promised. The EU in particular has taken a leadership role in reducing emissions, and has a serious shot at hitting their target of 40% reduction by 2030.

That is a truly astonishing scale of cooperation; the EU has a population of over 500 million people and spans 28 nations. It would seem like doing that should get us halfway to cooperating across all nations and all the world’s people.

But there is a vital difference between the EU and the world as a whole: The tribal paradigm. Europeans certainly have their differences: The UK and France still don’t really get along, everyone’s bitter with Germany about that whole Hitler business, and as the acronym PIIGS emphasizes, the peripheral countries have never quite felt as European as the core Schengen members. But despite all this, there has been a basic sense of trans-national (meta-national?) unity among Europeans for a long time.
For one thing, today Europeans see each other as the same race. That wasn’t always the case. In Medieval times, ethnic categories were as fine as “Cornish” and “Liverpudlian”. (To be fair, there do still exist a handful of Cornish nationalists.) Starting around the 18th cenutry, Europeans began to unite under the heading of “White people”, a classification that took on particular significance during the trans-Atlantic slave trade. But even in the 19th century, “Irish” and “Sicilian” were seen as racial categories. It wasn’t until the 20th century that Europeans really began to think of themselves as one “kind of people”, and not coincidentally it was at the end of the 20th century that the European Union finally took hold.

There is another region that has had a similar sense of unification: Latin America. Again, there are conflicts: There are a lot of nasty stereotypes about Puerto Ricans among Cubans and vice-versa. But Latinos, by and large, think of each other as the same “kind of people”, distinct from both Europeans and the indigenous population of the Americas.

I don’t think it is coincidental that the lowest carbon emission intensity (carbon emissions / GDP PPP) in the world is in Latin America, followed closely by Europe.
And if you had to name right now the most ethnically divided region in the world, what would you say? The Middle East, of course. And sure enough, they have the worst carbon emission intensity. (Of course, oil is an obvious confounding variable here, likely contributing to both.)

Indeed, the countries with the lowest ethnic fractionalization ratings tend to be in Europe and Latin America, and the highest tend to be in the Middle East and Africa.

Even within the United States, political polarization seems to come with higher carbon emissions. When we think of Democrats and Republicans as different “kinds of people”, we become less willing to cooperate on finding climate policy solutions.

This is not a complete explanation, of course. China has a low fractionalization rating but a high carbon intensity, and extremely high overall carbon emissions due to their enormous population. Africa’s carbon intensity isn’t as high as you’d think just from their terrible fractionalization, especially if you exclude Nigeria which is a major oil producer.

But I think there is nonetheless a vital truth here: One of the central barriers to serious long-term solutions to climate change is the entrenchment of racial and national identity. Solving the Tragedy of the Commons requires cooperation, we will only cooperate with those we trust, and we will only trust those we consider to be the same “kind of people”.

You can even hear it in the rhetoric: If “we” (Americans) give up our carbon emissions, then “they” (China) will take advantage of us. No one seems to worry about Alabama exploiting California—certainly no Republican would—despite the fact that in real economic terms they basically do. But people in Alabama are Americans; in other words, they count as actual people. People in China don’t count. If anything, people in California are supposed to be considered less American than people in Alabama, despite the fact that vastly more Americans live in California than Alabama. This mirrors the same pattern where we urban residents are somehow “less authentic” even though we outnumber the rural by four to one.
I don’t know how to mend this tribal division; I very much wish I did. But I do know that simply ignoring it isn’t going to work. We can talk all we want about carbon taxes and cap-and-trade, but as long as most of the world’s people are divided into racial, ethnic, and national identities that they consider to be in zero-sum conflict with one another, we are never going to achieve the level of cooperation necessary for a real permanent solution to climate change.

The temperatures and the oceans rise. United we must stand, or divided we shall fall.

A tale of two storms

Sep 24, JDN 2458021

There were two severe storm events this past week; one you probably heard a great deal about, the other, probably not. The first was Hurricane Irma, which hit the United States and did most of its damage in Florida; the second was Typhoon Doksuri, which hit Southeast Asia and did most of its damage in Vietnam.

You might expect that this post is going to give you more bad news. Well, I have a surprise for you: The news is actually mostly good.

The death tolls from both storms were astonishingly small. The hurricane is estimated to have killed at least 84 people, while the typhoon has killed at least 26. This result is nothing less than heroism. The valiant efforts of thousands of meteorologists and emergency responders around the world has saved thousands of lives, and did so both in the wealthy United States and in impoverished Vietnam.

When I started this post, I had expected to see that the emergency response in Vietnam would be much worse, and fatalities would be far higher; I am delighted to report that nothing of the sort was the case, and Vietnam, despite their per-capita GDP PPP of under $6,000, has made emergency response a sufficiently high priority that they saved their people just about as well as Florida did.

To get a sense of what might have happened without them, consider that 1.5 million homes in Florida were leveled by the hurricane, and over 100,000 homes were damaged by the typhoon. Vietnam is a country of 94 million people. Florida has a population of 20 million. (The reason Florida determines so many elections is that it is by far the most populous swing state.) Without weather forecasting and emergency response, these death figures would have been in the tens of thousands, not the dozens.

Indeed, if you know statistics and demographics well, these figures become even more astonishing: These death rates were almost indistinguishable from statistical noise.

Vietnam’s baseline death rate is about 5.9 per 1,000, meaning that they experience about 560,000 deaths in any given year. This means that over 1500 people die in Vietnam on a normal day.

Florida’s baseline death rate is about 6.6 per 1,000, actually a bit higher than Vietnam’s, because Florida’s population skews so much toward the elderly. Therefore Florida experiences about 130,000 deaths per year, or 360 deaths on a normal day.

In both Vietnam and Florida, this makes the daily death probability for any given person about 0.0017%. A random process with a fixed probability of 0.0017% over a population of n people will result in an average of 0.0017n events, but with some variation around that number. The standard deviation is actually sqrt(p(1-p)n) = 0.004 sqrt(n). When n = 20,000,000 (Florida), this results in a standard deviation of 18. When n = 94,000,000 (Vietnam), this results in a standard deviation of 40.

This means that the 26 additional deaths in Vietnam were within one standard deviation of average! They basically are indistinguishable from statistical noise. There have been over a hundred days in Vietnam where an extra 26 people happened to die, just in the past year. Weather forecasting took what could have been a historic disaster and turned it into just another bad day.

The 84 additional deaths in Florida are over four standard deviations away from average, so they are definitely distinguishable from statistical noise—but this still means that Florida’s total death rate for the year will only tick up by 0.6%.

It is common in such tragedies to point out in grave tones that “one death is too many”, but I maintain that this is not actually moral wisdom but empty platitude. No conceivable policy is ever going to reduce death rates to zero, and the people who died of heart attacks or brain aneurysms are every bit as dead as the people who died from hurricanes or terrorist attacks. Instead of focusing on the handful of people who died because they didn’t heed warnings or simply got extraordinarily unlucky, I think we should be focusing on the thousands of people who survived because our weather forecasters and emergency responders did their jobs so exceptionally well. Of course if we can reduce the numbers even further, we should; but from where I’m sitting, our emergency response system has a lot to be proud of.

Of course, the economic damage of the storms was substantially greater. The losses in destroyed housing and infrastructure in Florida are projected at over $80 billion. Vietnam is much poorer, so there simply isn’t as much infrastructure to destroy; total damage is unlikely to exceed $10 billion. Florida’s GDP is $926 billion, so they are losing 8.6%; while Vietnam’s GDP is $220 billion, so they are still losing 4.5%. And of course the damage isn’t evenly spread across everyone; those hardest hit will lose perhaps their entire net wealth, while others will feel absolutely nothing.

But economic damage is fleeting. Indeed, if we spend the government money we should be, and take the opportunity to rebuild this infrastructure better than it was before, the long-run economic impact could be positive. Even 8.6% of GDP is less than five years of normal economic growth—and there were years in the 1950s where we did it in a single year. The 4.6% that Vietnam lost, they should make back within a year of their current economic growth.

Thank goodness.