The Problem with Divestment: Helping Wealthy Investors Instead of Victims

A lot of social movements call for divestment of the shares of firms which are opposed to their goals. In particular, many colleges and universities have faced student protests demanding that college endowment funds divest from fossil fuel companies. However, they should be concerned about divestment’s actual effects.

If a group decides to sell off its shares of some Company XYZ, the price of the shares will fall. However, nothing has changed about Company XYZ’s expected future cash flows. Therefore, nothing has changed about investors’ valuations of Company XYZ. So when the share price falls, other investors simply get an opportunity to buy the shares for cheap. Net result: no damage to Company XYZ.

Furthermore, by creating this buying opportunity for other investors, what divesting groups are actually doing is transferring wealth to said investors. This usually means transferring wealth to wealthy individuals in the First World.

Of course, one argument could be that divestments act as public statements and make action by others more likely. A Harvard Political Review article argues that this was the case with divestments from South Africa in protest of apartheid: they had little financial effect, but helped raise awareness.

But divestments are public statements that cost money. What if universities instead aimed for high investment returns and donated the difference to efficient charities? (Possibly charities aimed at helping victims of whatever is being protested.) The result would be transferring money to effective causes instead of wealthy investors. And universities could still publicize their donations to charity as a way of raising awareness.

Let me reiterate: the main impact of divestment is that a few wealthy investors benefit, while the offenders are unharmed. Is that really ideal?

Elizabeth Stoker Bruenig Demolished Libertarians. And It Was Beautiful.

The New Republic staff writer Elizabeth Stoker Bruenig recently penned a devastating critique of libertarians, where she argued that the beliefs of self-described libertarians do not square with the central tenet of “freedom” that (allegedly) underlies libertarianism. She links to a wonderful Pew Research Center study, which she uses to base her takedowns and factually demolish libertarians bit. By. Bit.

Here is a play-by-play of her critique:

1) After quoting porn-famous Belle Knox on her move toward libertarianism after a strict Catholic upbringing, Bruenig notes that “Insofar as libertarianism is opposed to almost every feature of Catholic morality, Knox has certainly picked an appropriate politics of rebellion.”

Why this demolished libertarians: Catholicism teaches us to help the poor. Libertarians hate the poor, as evidenced by their desire to almost completely dismantle the safety net. Sure, they might argue government programs are inefficient or fail to stop poverty – but they only say this to cover up their elitist distaste of poor people. The truth is that even if these programs are inefficient, it doesn’t matter, because what they do is they show our commitment – as a society – to recognize the plight of the poor. You can’t put a price on dignity – and we want to restore the dignity of our lower class!

2) Relying on her careful reading of the Pew study, Bruenig concludes that “libertarians themselves do not appear to have a good sense of what libertarianism actually means.” You want evidence? Here is the evidence.

Why this demolished libertarians: According to the Pew study, 14% of Americans identify as libertarians. Furthermore, 11% of all Americans both identify as libertarian and at the same time know what libertarianism is. That means that 11/14 = 78% of people who identify as libertarians actually know what libertarianism means. And what does that mean? It means that more than 1 in 5 self-described libertarians doesn’t understand what libertarianism means!!

People who do not foolishly choose to identify with that political label of teenage rebellion are a different matter. The study notes that 57% of all Americans know what libertarianism means. If we remove the mere 11% of the population that is both libertarian and knows what the label means, that means that 46% of the population is both non-libertarian and knows what the label means. 46/86 = 54% of non-libertarians know what libertarianism is. That is, more than 2.5 out of every 5 self-described non-libertarians know what libertarianism means. And last time I checked 2.5/5 is, well, 2.5 times more than 1/5! If you eat 2000 calories a day, 2.5 times more than that is 5000 calories a day. Can you imagine that?!

3) Bruenig points out that “libertarians polled as far more supportive of police intervention in citizens’ daily lives, showing greater support for stop-and-frisk policies than the general population” [emphasis mine].

Why this demolished libertarians: Bruenig is not afraid to cite her sources, and even shows us a diagram from the study that backs her claim (red elements mine):

Notice that libertarians are a whole 1% more likely to allow police to stop/search all who look like crime suspects. And before libertarians start crying out that 1% “is within margin of error” or some made-up excuse like that (after all, they hate statistics because reality has a strong liberal bias), let me point out that 1% of the US population is more than 3 million people. That’s a lot of people, people!! The data proves it – libertarians, while pretending to be pro-freedom, actually support intervention into our lives far, far more than the general population!

4) Continuing, we learn that “A baffling quarter of libertarians surveyed believe homosexuality should be discouraged.” Do you know what I think should be discouraged? Libertarianism! If you didn’t think they were barbarians before, how can you have any doubt now? Libertarians think that homosexuals (or whatever awful slang word libertarians probably use at home to describe them) are no better than animals.

Why this demolished libertarians: Once again, just look at the source data, and the picture becomes clear: when it comes to hating gays, libertarians are unparalleled:

Notice that 26% of libertarians (even more than Bruenig had humbly cited!) think homosexuality should be “discouraged” – as if our neighbors and family members who are homosexual just “choose” to be gay and to be ostracized by society. Let me remind you, people, 26% is an enormous number!

How do non-libertarians compare? We just need to solve the equation 0.11*26 + x*89 = 31. Solving it, x=31.6, which means 31.6% of non-libertarians favor discouraging homosexuality. That means that almost 69% of non-libertarians are against discouraging homosexuality! If you need me to do the math for you, libertAynrians, the number 69 is more than 2.5 times bigger than 26! We see that 2.5 pop up again. Weird, huh?

5) Of course, Bruenig, being a master writer, also interweaves humor into her narrative: “Knox is only 19 years old, so we can hardly fault her for these contradictions.”

Why this demolished libertarians: Don’t you get it? Only teenagers could be libertarians, because teenagers are so immature and don’t know what the real world is like! Libertarians harbor ideas so far out of touch with reality, that even though they pretend to love “economics”, no libertarian (or person supporting any libertarian ideas) could ever win any legitimate prize in economics like the Nobel Prize.

6) She just keeps going for Belle: “For Belle Knox, freedom has to do with decriminalized sex work and fair pathways for women in employment—but both of those projects imply a level of proactive government regulation in business.”

Why this demolished libertarians: Can’t libertarians get it? Decriminalization of sex work means that we will need to regulate it. It’s obvious that, therefore, libertarians support a policy that would add regulation to the market: We’d go from a laissez-faire, completely unregulated and uncontrolled ban on sex work that requires no government intervention to a legalized industry with some regulations!

7) Bruenig calls the libertarians polled “jingoistic” – and once again her source backs her. When we look at the real, objective data, only 46% of libertarians think US involvement makes world problems worse, while the corresponding number for the entire US population is significantly higher: 40%!

Why this demolished libertarians: 54% of libertarians don’t think US involvement makes world problems worse. 40% of the general population understands that US involvement makes things worse. Would you rather be with 54 warmongers or 40 peaceful people? I thought so.

8) She just keeps going: “Libertarians who oppose government aid to the poor seem to desire freedom from taxes, but have no interest in whether or not the poorest are really free to exercise their rights to human flourishing when they can barely eat.”

Why this demolished libertarians: Read my lips: If you oppose the current welfare system, you think all poor people should die. Period.

9) Bruenig finishes the article off by telling us that “for genuine, invested activists like Knox, the evasiveness of the libertarian message should be a red flag.” A wise warning indeed.

Why this demolished libertarians: Belle is a teenager, and teenagers are stupid, so we know she’s genuine and invested. But other libertarians are not excused.

Class dismissed.

Immigration and the Zero Lower Bound: A Twist on the “Alien Invasion” Metaphor

I was thinking earlier today about the effect of immigration on interest rates. In particular, I thought of an unusual argument for immigration restrictions when short-run interest rates are at the zero lower bound.

Some New Keynesian economists have suggested that destroying productive capacity can raise current output in said circumstances. (For academic journal articles asserting this, see the beginning of this paper by Johannes Wiedland, also cited below.)

The reasoning is that a negative supply shock can lower expected production, thereby increasing expected inflation. When short-term nominal interest rates are stuck at zero, this has the effect of lowering expected real interest rates. This in turn causes people to spend more money now, raising output and employment.

Intuitive example: You have money in a bank account earning nearly zero interest. A hurricane forms, threatening the supply of various goods. What do you do? Simple: you take money out of the account and buy goods whose prices you expect to go up. The opportunity cost of doing so is minimal, and buying the goods before they go up in price makes you better off.

Paul Krugman’s example of an “alien invasion”: Nobel laureate economist Paul Krugman gave an infamous example of an attack by aliens on Earth, in which governments would scramble to spend money on defense. This example is a bit different from the one I gave, because the spending is done for the purpose of fighting off a potential supply shock, rather than just reacting to one.

However, in the case of the alien invasion, there is an expected possibility of aliens doing damage to the earth, and some diversion of resources towards fighting aliens instead of producing other goods. Both of these raise inflation expectations, lower real interest rate expectations, and increase present-day spending.

What does this have to do with immigration? When the economy is at the zero lower bound, it could make sense (under the model previously described) to further restrict immigration. This reduces expectations of real GDP, thereby increasing inflation expectations and inducing more spending.

Indeed, some people have referred to the existence of an “illegal alien invasion” (Google the term for examples); namely, of people entering the United States unlawfully. (Put aside the question of whether it is accurate to call mostly-peaceful migration an “invasion”.) But, unlike Krugman’s, this “alien invasion” would lower current output! With more immigrants adding to future real GDP, and short-term nominal interest rates stuck at zero, people would expect that goods will be cheaper in the future than they previously thought, and would hoard more money as a response.

A few reasons why I don’t actually endorse this argument for immigration restrictions:

  1. Even accepting the described view on supply shocks, one might not want to trade off future production for present production. Krugman was joking with his suggestion of faking an alien invasion, and it’s unfair to say that people who endorse this model don’t care about the long term at all.
  2. There are empirical issues with the claim that negative supply shocks at the zero lower bound are expansionary. Johannes Wieland of UC Berkeley argues in the previously linked paper “Are Negative Supply Shocks Expansionary at the Zero Lower Bound?” that “financial frictions” prevent this effect from working. He claims that negative supply shocks reduce the value of banks’ balance sheets, thereby constraining their lending and preventing the positive effect on aggregate demand from taking place. Using a general equilibrium model with these “financial frictions” built in, he finds that negative supply shocks at the zero lower bound do hurt short-run output. More research here may be needed, but his case seems plausible.
  3. There are better ways of dealing with the zero lower bound. I don’t want to get into my views on monetary policy here, but it should suffice to say that most people across the various schools of thought find there to be better ways of getting out of the zero lower bound than deliberately destroying productive capacity.
  4. Immigration could raise returns on capital and investment demand, thereby raising interest rates. Generally speaking, expanding the supply of labor is expected to raise the return on capital by acting as a complementary good. However, I say “could”, because the complementarity between labor and capital is very complex, and there are cases in which immigrants act as substitutes for capital. Dartmouth economist Ethan Lewis has done some work on this subject; see, for instance, “Immigration and Production Technology”.

I can’t say I find the “restrict immigration more at the zero lower bound” argument persuasive, but it is at least interesting, and I think I am the first to suggest it.

Could Privilege-Checking Lead to “Conservative” Conclusions?

Here I will use “conservative” loosely to refer to the general “personal responsibility” and “pulling yourself up by your bootstraps” attitudes the American right might generally support.

My foray into privilege theory has led me to ask myself what some of its implications for direct action are. That is, given what we know about privilege, and assuming that we care about people who are underprivileged, what should we do about it?

We begin again with the framework of privilege I discuss in my “Formalizing Privilege” article: that privilege is the combination of genetic and environmental factors that cause one’s success/satisfaction/power in life. Using this definition, we ask ourselves what we can do to alleviate the plight of the underprivileged. This article is not meant to be the end of this conversation, but merely an observation that might have otherwise gone unnoticed.

One of the central questions in this discussion is which privilege is the “most important one.” One way we can study this topic, as with everything else in science, is to vary a single variable while holding all other ones fixed. That is, we vary one privilege and we fix all others and observe the outcome. For example, if we’re interested in how important race is (on the margin), we take people who are identical in all ways except for in their race and we see how their lives turn out.

This analysis is difficult to perform because we generally do not have people who are identical except for one characteristic, and the origins of various privileges can be very difficult to notice (and are often unobservable, especially given our current data sets). Still, I wish to present one case study and discuss its implications: that of Ben Carson, as I learned about him from the book Gifted Hands. I hope that the shortcomings of extrapolating from this data set of size one are kept starkly in mind, while the important lessons are also taken to heart.

Ben Carson grew up fairly underprivileged:

– He was a black child in Detroit

– His mother raised him and his brother (sometimes on three low-paying jobs) without his father, while at times away for psychiatric treatment

– His mother had married at 13 and had no more than a third grade education.

– His school environment was not conducive to growth and self-empowerment

– He was teased by his white classmates (and sometimes his teachers) and he at one point believed he was not smart enough to do well in school

I initially had chosen the phrase “as underprivileged as they come” to describe him, though in the spirit of accuracy I decided not to use it, since it’s probably always possible to be less privileged. Still, it comes close.

We know what ended up happening to Carson: he became one of the world’s leading neurosurgeons, and he was a pioneer in new types of brain surgeries. Given all his underprivileges, what gives?

It’s possible to attribute all of this to chance – Carson just happened to be lucky and all the steps that led to his eventual success were a stroke of luck. This is theoretically possible, but I don’t find it particularly compelling.

The other explanation is that he was able to overcome the negative aspects of his environment through the positive ones – most notably, his mother’s influence. His mother instilled in him the values of hard work and determination and always pushed him to give his best. I would give a longer description of all of the values she stressed, but it would likely be variations on the main theme of hard work, so I won’t insult the reader’s intelligence by trying to influence him or her by repetition. Instead, let’s look at what conclusions we can draw.

It appears, at least in this case, that the values instilled in a person are so strong that they may very well overpower all other external underprivileges (which in Carson’s case were many – being a poor, black kid in Detroit under a single mother who had psychiatric problems and had to raise two children). Naturally, it’s unreasonable to expect that all kids who have these influences can become as successful as Ben Carson. But Carson’s story is an interesting case study where we have a mix of severe underprivileges that are counteracted by the value of hard work.

The “policy” recommendation here becomes apparent: teach kids “conservative” values that are traditionally associated with the American right: work hard, keep your course, study in school, be responsible, and pull yourself up by your bootstraps. This can be implemented either culturally (through a shift in what individuals in society choose to teach their children) or governmentally (through government edicts to emphasize hard work and personal responsibility in school and propaganda to do the same outside of school).

What I’ve done here is Type 2 privilege checking, as defined in my original article, which seeks to understand causal pathways in society that lead to people’s success. That is, I checked Dr. Carson’s privilege to see how other people could emulate him, and his story is a testament to conservative values. Do I believe that these should become government policy? No – I don’t favor social manipulation by the government of any kind, though I personally find the ethic of hard work to be empowering myself. I merely point out the conclusion from checking Dr. Carson’s privilege: if we want underprivileged people to do better, one way to achieve this is a cultural shift to the right. Do I think we should do this? Irrelevant – it’s what privilege theory suggests, and that’s all I mean to do in this article: see another conclusion of privilege theory. Of course, this doesn’t mean there aren’t other ways to help underprivileged people – either governmental or voluntary. However, for people who actually care about helping the underprivileged, this is a strategy that can be put into action without relying on the power of government. As such, it might be much more realistic to implement – and increased effort on the margin would lead to greater marginal results.

A Question on Human Rights Abuses and Secession

It is a fairly common belief that secession is legitimate in cases where it is necessary to stop human rights abuses. There is a somewhat less common view that secession is legitimate if it is supported by a majority or supermajority of people in the seceding region, as long as it does not create human rights abuses in that area. (See, for instance, Christopher Wellman on the matter, and Ilya Somin’s discussion relating to Crimea.)

However, what about the possibility of secession creating human rights abuses in the country which a region is seceding from?

Here’s an example: suppose some of the more anti-slavery Northern states in the U.S. had seceded in the decades before the Civil War. (There was some support for this, since many Northerners viewed the Fugitive Slave Act and wars fought for the expansion of slavery as unjust.) Suppose then that it had swung the remainder of the U.S. in a pro-slavery direction. Perhaps some results could be the expansion of slavery into the West, or more strictly enforcing the Fugitive Slave Act in non-seceding free states.

Could one then argue that the seceding states have an obligation to stay in the Union and keep pro-slavery policies from taking hold?

My current thought is that, since it can be very difficult to predict the outcomes of any given secession, a seceding region should not be blamed for these kinds of issues occurring.

In the previous example, it’s also quite possible that the remaining U.S. would have difficulty expanding slavery into the West without Northern military support. It’s possible that the Fugitive Slave Act would be weaker, since escaping slaves would be closer to permanent safety. (Getting to, say, Wisconsin, is easier than going all the way to Canada.)

Nonetheless, it does seem like this question could pose some issues for deciding when secession is appropriate, both in mainstream and less-mainstream theories. Feel free to post your ideas in the comments.

“Money is Not Speech” Misses the Point

The news of the U.S. Senate Judiciary committee approving a constitutional amendment allowing Congress and the States greater power to restrict political spending may bring attention to the issue of campaign finance. A fairly popular phrase in populist circles (especially on the left) used in favor of campaign finance restrictions is “money is not speech“.

Notably, former Supreme Court Justice John Paul Stevens used the phrase when describing his opposition to the Citizens United decision, which allowed corporations and other associations to make independent expenditures on political campaigns. Maryland State Senator Jamie Raskin even claimed that treating the spending of money as free speech would require that prostitution be protected as a form of free speech.

Frankly, the “money is speech” characterization is disingenuous. The point is not that spending money on things generally is a sign of one’s preferences and thereby a form of “free speech”. The point is that spending money on resources and labor directly used in the act of communication is protected.

For instance, most publishing companies are corporations. If a publishing company spends money from its general treasury to publish a book containing political advocacy, should that act be protected under the First Amendment? I would say so. In this case, the free speech rights of the authors would be at stake.

And yet this not was the view of the government in Citizens United (see this link, pp. 26-29). The case was later re-argued, and the government decided that there might be other reasons justifying a challenge to restrictions on book publishing (see this link, pp. 64-65), but the same basic argument still applies to broadcast media, which was the issue in Citizens United. Should a TV broadcaster be allowed to spend its general treasury funds on producing and distributing political content?

When the issue is phrased in terms of spending money on speech, rather than just spending money, it becomes clear that restricting political spending is, in fact, a form of censorship.

Two Thirds of Nordhaus’s 1999 DICE AGW Damages Are Based on Unsubstantiated Guesswork

William Nordhaus is one of the top experts on the economics of climate change and for a long time has worked on his series of DICE models (Dynamic Integrated Climate-Economy models) that examine how standard predictions of the effects of climate change on climate variables (such as global mean temperature) will impact the economy. His work is important because DICE is one of the three Integrated Assessment Models (IAMs) of climate-economic interaction that the government’s Interagency Working Group on Social Cost of Carbon uses in its analysis of the impacts of climate change. In other words, DICE is one of the three models used to calculate the Social Cost of Carbon (SCC), which is meant to represent the damage caused by one additional ton of CO2 in the atmosphere. The SCC was devised so that the government could weigh different strategies to slow down COemissions and (in theory) reject any that cost society more than the damage caused by the COemissions they prevent. In this post I highlight a problem economist Robert Murphy had found in Nordhaus’s 1999 version of DICE and add an observation of my own. To be clear, Nordhaus has since updated his model, and the issue likely does not persist, though I have not yet read the 2013 DICE specifications.

A long time ago, I was reading Murphy’s 2009 article Rolling the DICE: William Nordhaus’s Dubious Case for a Carbon Tax, and I was struck by the section discussing the possible economic damages from low-risk catastrophic climate scenarios (such as the shutting down of the thermohaline circulation of heat and salt among the world’s oceans). These are, again, doomsday scenarios that scientists do not believe will happen, but to which they still assign a low probability of occurring. These numbers are needed to create the model’s damage function, which describes the loss of Gross World Product (GWP – also referred to as world GDP herein) due to increased temperatures. How did Nordhaus get his probabilities for these catastrophic scenarios? He relied on a survey of experts he published in 1994, worded as follows:

“Some people are concerned about a low-probability, high-consequence output of climate change. Assume by ‘high-consequence’ we mean a 25 percent loss of global income indefinitely, which is approximately the loss in output during the Great Depression. (a) What is the probability of such a high consequence outcome for scenario A, i.e., if the warming is 3 degrees C in 2090 as described above? (b) What is the probability of such a high consequence outcome for scenario B, i.e., if the warming is 6 degrees C in 2175 as described above? (c) What is the probability of such a high consequence outcome for scenario C, i.e., if the warming is 6 degrees in 2090 as described above?”

Yet the results from 1994 will not do in 1999, since Nordhaus claims that new research has placed increased emphasis on the possibility of these catastrophic events. What does he do, then? And this is where Murphy picks a fight with him. To cite Nordhaus,

“To reflect these growing concerns, we assume [that] the probability of a catastrophe with 2.5 C warming is double the estimated probability for a 3 C warming from the survey, that the probability associated with a 6 C warming is double the survey estimate, and that the percentage of global income lost in a catastrophe is 20 percent higher than the figure quoted in the survey.”

Murphy summarizes what has happened as follows:

“To restate the issue: Nordhaus in 1994 asked experts to estimate (among other things) the probability of global GDP loss of 25 percent in the event of 3.0 C warming […]. The surveyed experts gave him their answers, from which he computed the mean. By 1999, further research had made these scenarios seem more plausible or catastrophic. So Nordhaus and Boyer took the original average of probabilities reported by the experts, doubled it, and then assigned this new figure as the probability for a 30 percent loss of GDP rather than the 25 percent the experts had been told to consider, for a less significant warming of 2.5 C rather than the 3.0 C mentioned in the original survey. […] More recent research suggests that at least some of these catastrophic scenarios were false alarms”

Why does it matter that Nordhaus apparently arbitrarily took the results of the survey of experts, doubled their answers, and then used these as probabilities for a different change in temperature and a different economic impact? Nordhaus claims that a 2.5C temperature increase would result in a loss of 1.50 percent of world GDP. And yet, 1.02 percentage points of these 1.50 percent are due to the low-probability catastrophic scenarios discussed above. This means that 68% of all the economic damages are based on numbers that Nordhaus arbitrarily manipulated.

So far so good – this has been Murphy’s critique (which I consider strong enough of a challenge to the model’s results). Yet I decided to dig a little deeper and look at how the 1994 numbers were obtained in the first place. They come from Nordhaus’s 1994 paper “Expert Opinion on Climate Change” in the American Scientist. In this paper, Nordhaus asked 22 experts their opinions on various questions relating to the effects of climate change on the economy. Three refused to participate, and of the nineteen remaining, nine were a mixture of economists, four were other social scientists, five were natural scientists and engineers, and the last one was Nordhaus himself. Again, it must be emphasized that this is not a review of literature of studies attempting to calibrate damage functions to observed warming, or at least to come up with plausible costs for disasters whose workings are scientifically described. No – the study merely asked nineteen experts in the field what they thought of the question [1].

We need to stop and consider how difficult the scenarios posed are: For example, in scenario A, respondents are asked how likely it is to have a 25% drop in world GDP in the year 2090 if there is 3 C warming. In a simple survey, respondents are asked to tackle a problem worthy of the whole literature – they are expected to take into account immigration flows, capital accumulation, technological adaptation, and a variety of low-probability catastrophic events we know of (and even ones we have not yet even conceived of) through the year 2090. They’re expected to be able to model the complex dynamics of the global market, advancements in science, and the catastrophic events due to precisely 3 C of warming. Nordhaus mentions in several places that there is much disagreement even among these experts on the economic impacts of catastrophic events, as seen in the spread of guesses for his questions. He notes that

“[o]ne respondent suggested whimsically that it was hardly surprising, given that the economists know little about the intricate web of natural ecosystems, whereas scientists know equally little about the incredible adaptability of human economies.”

And yet this does not seem whimsical at all, but a fundamental flaw in the methodology of the study. Natural scientists know very little about modeling economies and the ability of economies to respond to shocks. Similarly, economists are not intimately aware of the details of the consequences of climate change. Let’s look at what it would take to give an answer for Scenario A. One would first need to decide on the probability of various catastrophic outcomes due to 3 C in 2090 (a difficult enough endeavor). Then, one would need to estimate the economic impact of each catastrophic outcome to see whether it makes the 25% cutoff. The ones that do are all added together and this resulting probability is given as the answer.

In this deconstruction of the problem, we can see why the “whimsical” comment of the respondent above is not so whimsical at all – the question requires one to answer two very difficult subquestions, where each is focused on an entirely different field – one on climatology, the other one on economics. Only when these two are combined can the answer given be fully informed. How can an economist accurately answer the first part of the question – on the probabilities of different known (and even unknown!) catastrophic events. How can a natural scientist adequately guess the economic damage due to a climate event? Not only this, but the respondents were asked to give their subjective probabilities to these catastrophic events without having conducted any studies on this specific question, but merely as a matter of opinion. Yes – expert, informed opinion, but no matter how much of an expert someone is, when giving a probability to a 25% reduction in GWP due to 3 C warming in the future of 2090, which has unknown adaptive technology, her best guess will still be a fairly uninformed guess. Some respondents do mention technology as the big unknown:

“What is missing most is an understanding of the role of technology, of how society will change as technology advances. If we had been concerned with global warming in the 1890s, it would have concerned transportation by horses rather than automobiles. It is impossible to contemplate what society will be like a century from now as technology changes.”

Another writes

“Technology will develop to adjust to and accommodate many of the climatic changes and even provide approaches to countering warming effects. However, projecting technological changes a century or two into the future is hazardous at best. All we can really say is that there will be technological changes and that as in the past they will probably offset adverse effects to some degree.”

I cite this not to dismiss concerns over warming, but to show just the enormity of the task the experts were asked to perform – “impossible” by the words of some of them (in the case of forecasting technological changes). A major rainstorm in the distant past would have done much more damage to the livelihood of the public than it would today, for example. Why? We have sturdier buildings. This shows that the damage by natural events depends on the technological progress of a society very strongly. Nordhous quotes one of the respondents, who shares my main concern:

“I must tell you that I marvel that economists are willing to make quantitative estimates of economic consequences of climate change where the only measures available are estimates of global surface average increases in temperature. As [one] who has spent his career worrying about the vagaries of the dynamics of the atmosphere, I marvel that they can translate a single global number, an extremely poor surrogate for a description of the climatic conditions, into quantitative estimates of impacts of global economic conditions.”

Combining this with Murphy’s point that Nordhaus simply decides to double the values acquired from the survey and use them as answers to a different question, Nordhaus’s model (and its policy implications) becomes dubious. To reiterate what has happened: Nordhaus created a model where two-thirds of the damages from climate change are estimated from a survey asking a mix of scientists and economists their subjective opinion on how likely it is for a 3 C increase in 2090 to cause a 25% drop in GWP given unforeseeable technology, unforeseeable geographical population spread, unforeseeable gradual adaptation, and unforeseeable economic conditions, averages the opinions of these people, some of whom point out the precariousness of asking experts to weigh in on issues they know little about, and then takes this average, doubles it, and uses it to represent the chance of a catastrophic event resulting in a different scenario – a 30% drop in GWP due to a 2.5 C increase. In this case, “unsubstantiated guesswork” might be putting it lightly.

Once again, Nordhaus has a 2013 DICE model out, which likely does not have the above fatal mistakes. I did not intend this post to make light of the danger of climate change (with which I am not well-acquainted, not being a climate scientist myself), but merely to show the importance of looking at assumptions in our models, especially when they have such large impacts on the results of the model – and when the world looks to you for guidance on the issue.


[1] Here’s an analysis I would consider to be an honest attempt at such an endeavor: Say we’re trying to assess the damages due to an enormous rise in sea levels. We’d begin with a map of the inundated areas and assess the current property values. This amount would then get adjusted to account for possible appreciation in the housing market. Afterwards, we might try to set up a model of housing investment, price changes, and population growth and migration to look at how much the demand for housing would increase across the entire world, and, hence, how much a reduction of usable housing area would cost the economy. We’d also need to take into account adaptive behavior that some areas might take to prevent the damages from a sea level rise (walls?). And so on. And this is just for sea level rise! In short, the survey respondents were asked to create a general equilibrium model of everything in the world and extend its predictions out to the year 2090 – a task worthy of a team of hundreds of economists and years of planning and debate (and even then, the model would still fall short).