I agree that what you’re saying could in principal be a problem, but I don’t think that’s how its actually played out in the case of the IPCC. I think there are many reasons why climate change is a politically polarized issue, and I personally don’t think that the IPCC played a material role in increasing polarization directly or indirectly (and IMO their impact went in the other direction for the reasons I outlined above).
DannyBressler
Karma: 410
Thanks for this comment! I am definitely in favor of country-level efforts to address GCRs and to produce reports like this one. The same way that the U.S. produces the National Climate Assessment despite there also being IPCC reports. In this case, I think those two efforts are more complimentary than cannibalistic. E.g., folks that work on the National Climate Assessment in the US often also work on the IPCC and doing the work of organizing/prepping for one helps with organizing/prepping for another. And having an international IPGCR effort may also encourage countries to undertake their own national GCR efforts.
Also, my sense is that the IPCC tends to be more conservative in its findings/statements compared to the National Climate Assessment because it requires a level of buy-in and sign off from its 195 member countries, whereas the National Climate Assessment is produced by a single country. My hypothesis is that a similar dynamic may end up being the case here, where the IPGCR may produce findings that are more conservative than what a single country might produce. But this is still helpful because it gives a sense of which sorts of policies may be palatable globally.
In terms of this effort being a potential cause of political polarization on GCRs, my sense is that in the climate case, the IPCC has not been a driver of the political polarization we’ve seen. Of course, there has been a lot of political division on climate action, but my sense is that the IPCC itself has played little role in causing this. On the contrary, I’ve seen the IPCC as playing a major role in effectively establishing a set of basic knowledge (and corresponding levels of confidence, as their findings are always given with a level of confidence) around climate change, that those skeptical of climate action find it hard to argue with. There is a lot more that is less certain those those skeptical of climate action now debate over (e.g. the benefits and costs of climate action, ability to coordinate global policy to overcome free-riding, etc.), but I think the IPCC has been useful in making it difficult to credibly argue with some of the more basic climate knowledge where there is a good deal of consensus. I often here speakers that are skeptical of climate action going out of their way to emphasize that they agree with key findings of the IPCC to avoid seeming unreasonable.
I see the IPGCR as producing reports that convey areas of consensus, disagreement, and uncertainty among experts from around the world. On a given topic, there might be a lot of uncertainty and disagreement, but there might be some areas where there is perhaps a surprising amount of consensus, and uncovering and convering that information is useful. And if other similar national reports also come to similar findings, that could be helpful in identifying productive areas where progress can be made.
FYI—OMB has extended the comment period deadline for Circular A-4 to June 20th https://twitter.com/jacklienke/status/1665818966818799617?s=20
However, the Circular A-94 comment deadline is still today.
A-4 comment submission link: https://www.regulations.gov/document/OMB-2022-0014-0001
A-94 comment submission link: https://www.regulations.gov/document/OMB-2023-0011-0001
I’m pretty late to the party here, but I want to say I really enjoyed the piece! Your piece came out only three weeks before the big draft overhaul to the way that the U.S. does benefit-cost analysis came out, which is in a document called Circular A-4. I think there is a lot I’d change around the choices in the analysis, particularly in light of the new draft A-4 Guidance (most of which goes in favor of putting more weight on catastrophes):
The old A-4′s use of a 7% discount rate on capital didn’t make sense because the 7% includes other factors outside of time preference (in particular risk aversion). The new A-4 has a much better treatment of discounting capital: which is applying a shadow price of capital adjustment, which is somewhere between a factor of 1-1.2 (so it’s not too much of an adjustment in any case). The upshot of all of this is that, based on the new A-4, you should be using a 1.7% discount rate for impacts out to 30 years, which is drastically different than the 7% discount rate that you were using and which will put more weight on the future (and appropriately so from the descriptive point of view to reflect people’s tradeoffs between money now and money in the future in capital markets).
For impacts beyond 30 years, standard economic theory and the new A-4 suggest that you should be using a declining discount rate to account for future interest rate uncertainty (see my brief description here). The A-4 preamble has a proposed schedule of declining discount rates, which goes down to 1% 140 years in the future. This will also place more value on the future.
President Biden’s Presidential Memorandum and the new A-4 are quite clear (see summary of A-4′s temporal scope of analysis section) that the interest of future generations should be taken into account when they will be impacted by important benefits and costs from some policy. In fact, the U.S. had previously been accounting for the impacts of climate change out to 500 years in BCA (in the Obama, Trump, and Biden administrations) through the use of the Social Cost of Greenhouse Gases, so impacts on future generations had been taken into account in that context, and should be taken into account in these other contexts as well, as discussed in the new draft A-4.
Much of your analysis seems to only look at the direct impacts on Americans. However, A-4 has a robust discussion around the conditions under which it is important for analysts to include global impacts, such as “regulating an externality on the basis of its global effects supports a cooperative international approach to the regulation of the externality by potentially inducing other countries to follow suit or maintain existing efforts.” This recognizes that global externalities/risks like pandemics, biosecurity, climate change, etc. require international regulatory cooperation. If, e.g., a new global pandemic is caused by poor biosecurity regulatory oversight in other countries, this harms Americans. Both because Americans will get sick and die, but also because disruptions in other countries will cause significant harm to the global economy, global trade, and global stability that will in turn harm Americans. Just as poor biosecurity regulatory oversight in the U.S. causing a pandemic will cause harm in other countries for the same reasons. Note that this is also the approach that the U.S. Government has taken to account for climate change in BCA through the Social Cost of Greenhouse Gases by considering global damages from climate change and not just domestic damages. As that document states, global externalities like greenhouse gas emissions and biosecurity policy imply that the whole world enjoys the benefit of one country’s decisions to reduce the harm from the global externality, and therefore “the only way to achieve an efficient allocation of resources for emissions reduction on a global basis—and so benefit the U.S. and its citizens and residents—is for all countries to consider estimates of global marginal damages” from the externality as well as the global marginal benefits of taking actions to reduce the externality.
Although your post is about risks, I didn’t see mention of accounting for Risk Aversion, which is one of the most consistent features of human preferences and should be reflected in BCA. The draft A-4 instructs BCA practitioners to explicitly account for uncertainty when doing BCA as well as risk aversion across that uncertainty. This ends up placing more weight on the benefits that help to avoid catastrophes, and thus would tend to favor policies that reduce the probability of catastrophes (e.g. pandemic preparedness).
And finally, much of your analysis seems to hinge on probabilities for catastrophes that come from e.g. the EA community or Prediction Markets. Because you choose to account for a very limited scope of impacts across time and space at a very high discount rate, those probabilities end up having to do a lot of work for the analysis to yield net benefits. My sense is for the purposes of BCA for U.S. regulatory impact assessments, these probabilities may be viewed as too speculative (at least for anthropogenic risks) and may be challenged in getting through the various processes that BCAs for regulations must go through including public comment, OIRA review, and then ultimately litigation in court where most rules are inevitably challenged. Fortunately, A-4 has a tool that provides a way forward in this situation: Break Even Analysis. Break-even analysis provides a way forward when there is a high degree of uncertainty/ambiguity in important parameters, and you need to determine what those parameters would need to be for the policy to still yield positive net benefits. This is particularly relevant for catastrophic events: “For example, there may be instances where you have estimates of the expected outcome of a type of catastrophic event, but assessing the change in the probability of such an event may be difficult. Your break-even analysis could demonstrate how much a regulatory alternative would need to reduce the probability of a catastrophic event occurring in order to yield positive net benefits or change which regulatory alternative is most net beneficial.”
To Summarize, I think U.S. BCA practice actually offers a much wider variety of tools for assessing catastrophic risks, which benefits the interest and welfare of Americans, and those tools should be utilized.
I think you’re referring to the difference between Executive Order 12866 (from the Clinton Administration in 1993) and Executive Order 12291 (From the Reagan Administration in 1981).
The Office of Management and Budget is only asking for comment on Circular A-4 and Circular A-94, not on Executive Order 12866, so I would not suggest making comments on that.
Also, the administration released a new Executive Order 14094 on the same day that the A-4 and A-94 updates were released, which reaffirmed executive order 12866 but made some important changes, for instance increasing the definition of significant regulatory action from $100 million to $200 million, which in my view is a reasonable/helpful thing to do to save administrative capacity. Executive order 12291 required OIRA to look over every regulatory impact assessment regardless of the size, which in consequence meant that they were in inundated with reviewing ~2400 rules a year and therefore it was more difficult to carefully review proposed regulations. OMB is not seeking comment on Executive Order 14094, so I would not suggest making comments on that either.
The part of Executive Order 12866 that is highlighted in the draft A-4 update is: ”...in choosing among alternative regulatory approaches, agencies should select those approaches that maximize net benefits (including potential economic, environmental, public health and safety, and other advantages; distributive impacts; and equity), unless a statute requires another regulatory approach.” So they are interested in maximizing net benefits. You’re right that there is one line in 12866 (which is a 10-page order) that says “Each agency shall assess both the costs and the benefits of the intended regulation and, recognizing that some costs and benefits are difficult to quantify, propose or adopt a regulation only upon a reasoned determination that the benefits of the intended regulation justify its costs.” My sense is that this was written because there are often important categories of benefits and costs that are difficult to place a reliable value on (or at least one that would get through OIRA review and taken seriously if the regulation is challenged in court). But it’s still important to state and discuss important unmonetized in BCA (this is covered on pages 43-47 of the new draft A-4.). Catastrophic impacts that have highly uncertain probabilities often fall in this category (see my discussion in the main post around how break-even analysis is useful in this context). 12866 is making sure that analysts have the option to account for these unmonetized benefits and costs.
In practice, my sense is that agencies do typically want to show that monetized benefits exceed costs, because this makes it more likely that things will pass OIRA review and that the regulation will make it through the courts. I’d highly recommend this interview with OIRA chief Ricky Revesz if you’re curious on this: a typical administration has ~70% of its rules upheld when challenged in courts, and a strong benefit cost analysis supporting the rule certainly helps with that process. And in any case, 12866 and the draft A-4 does direct agencies to choose the option that maximizes net benefits. My sense is that the one line of language around benefits justifying costs was intended to address situations where important benefits or costs cannot be reasonably monetized in a way that would pass OIRA review/make it through litigation but are still important. But even so, my sense is that it is rare for monetized costs to exceed benefits in BCAs, and that there was not some type of step-change when 12866 was passed in 1993 where a bunch of regulations were proposed with monetized costs exceeding monetized benefits.
So to summarize, I actually think that small change in language from 12291 to 12866 thirty years ago was on net a good thing and not a bad thing, and in any case they are not asking for comment on the executive orders. But if there are things in the draft A-4/A-94 you like (or not) I’d highly recommend writing a comment.
I think marginal climate interventions are in the conversation for being competitive on a global health and wellbeing basis. By that I mean ignoring the chance of existential risk from climate change, marginal climate interventions are in the conversation for being competitive just based on the expected impacts of climate change, which will be concentrated on the world’s poorest people. This is provided that you can reduce marginal emissions on the order of ~$1 per ton (which I know some folks have said is a reasonable estimate for targeted marginal emissions reductions… my expertise is much more on the climate impacts side so I’ll keep that as given for now).
Note that DICE-2023 has multiple aspects that cause it to understate the benefits of emissions reductions compared to, e.g. OP’s Global Health and Wellbeing Framework:
-DICE counts a dollar to the poorest people on the planet the same as a dollar to a billionaire. Whereas if you are interested in determining the impact on wellbeing, you’d want to account for diminishing marginal utility—i.e. a dollar of climate damages is much more harmful to a very poor person than to a very rich person. The way to do this in benefit-cost analysis is called distributional or welfare weighting, which is, e.g., what Open Philanthropy’s Global Health and Wellbeing Framework does. Distributional weighting was just sanctioned by the US Government for use in benefit-cost analysis (provided that the new draft guidelines are not altered in the review and public comment process), and it is already used in the UK and Germany. Because climate change is projected to hurt the global poor much more than the rich, the SCC goes way up when you do distributional weighting.
-DICE continues to ignore the impact of climate change on temperature-related mortality. The latest IAMs that were used in the November 2022 EPA SC-GHG update suggest that ~50-80% of the SCC comes from temperature-related mortality. And this is when lives are valued proportionally to their income so that, e.g., 50 Congolese deaths are counted the same as 1 Belgian death. If you valued lives equally, this percentage would be much higher. The mortality damage functions in those studies are similar to the mortality damage function from my 2021 Mortality Cost of Carbon article, which finds that reducing 4,434 tons in a higher emissions scenario saves one life over the next 80 years and 9,318 tons in a lower emissions scenario (net zero by 2050). I.e. if you can remove a ton of carbon dioxide on the margin for $1, you would save one life in expectation for $4,434 in the high emissions scenario and $9,318 in the low emissions scenario. And this is only the benefit of reducing emissions on temperature-related mortality and ignores all of the other benefits from reducing emissions. Some of those benefits are captured in Social Cost of Carbon estimates (e.g. the projected impact of climate on staple crops is included in the GIVE and DSCIM models, as is sea level rise coastal impacts, and the impact on energy use), but many impacts that we have reason to believe could be large are not included (e.g. the impact of climate change on ocean acidification, biodiversity, conflict, and much more).
So these various factors I think put marginal climate interventions into the discussion as being cost-effective from a global health and wellbeing perspective.
Thank you for sharing! For those interested in this topic, I’d highly suggest making a public comment on the new drafts of Circular A-4 and Circular A-94.
I think the public commenting instructions should be up on OMB’s Federal Register page soon (it looks like tomorrow and the commenting period typically lasts 45-60 days): Federal Register :: Agencies—Management and Budget Office .Public comment is an important part of the regulatory process, and agencies actually do pay attention to what people say. In addition, comments that are supportive of the approach taken are equally as valuable as critical comments.
No worries! I’m glad you found the paper useful and interesting!
The mortality cost of carbon is just the number of excess deaths from temperature-related mortality in units of excess deaths from emitting one metric ton of CO_2. So it’s just excess deaths and nothing else. The social cost of carbon is the full monetized value of all climate impacts from emitting one ton of CO_2, which includes the monetized value of those excess deaths in addition to other sources of climate damages. You can see that before the model accounted for temperature-related mortality, the social cost of carbon was $37, but after accounting for temperature-related mortality, it is $258. However, note my caveat from the conclusion: “It is important to note that recent literature has identified other shortcomings in the DICE model including other issues with the climate-economy damage function and the climate module. Besides adding the effect of climate change on mortality and subsequent feedbacks, DICE-EMR takes the rest of the DICE model as given without updating other factors.”
It’s hard for me to determine how much the different simplifying assumptions from your back-of-the-envelope formula are affecting your estimate. The linearity assumption is certainly causing a big difference because the system is highly convex. Also, the DICE-EMR model has the DICE climate model built into it that can show the climatic effect of changes in emissions. I’m not sure how much error you’re introducing with the back-of-the envelope climate assumptions, but that could also be an issue.
All this to say, if estimating the marginal impact (either the mortality cost of carbon or the full social cost of carbon) were as simple as a back-of-the envelope calculation, then there wouldn’t be a need to give William Nordhaus the Nobel Prize for his work on the original DICE model (the first one for environmental economics), nor for me to do this work. I think Louis Dixon’s original post is basically all you need to do for this exercise (at least for leveraging my paper’s results). Or as @jh suggested above, a $1/ton estimate just gets you to $4.4K per life saved using my paper’s results.
Also, see this one quote from the end of the paper: “Separate from policy, the MCC and SCC can be useful in informing the decision-making of individuals, households, companies, charities, and other organizations in determining the social impact of the emissions generated by their activities. The emissions contributions of these groups are usually marginal relative to the aggregate emissions of the world economy from the industrial revolution through the twenty-first century. Therefore, the social impact of changes in their activities that either reduce or increase emissions should be quantified using estimates of marginal impacts: i.e. the SCC and the MCC.”
Thank you for this post on a very important topic! And thank you for the kind words on my Mortality Cost of Carbon paper.
I think that, at least from the perspective of using my paper, the analysis is actually much simpler than what you do above. Instead of using the 83 million cumulative 2020-2100 excess deaths, use the mortality cost of carbon itself: i.e. the number of lives saved per ton of carbon dioxide reduced, which is provided by the paper. So instead of the equation you show above, the equation now becomes:
Marginal Cost Per Life Saved = (Marginal Cost Per Ton CO_2 reduced)/(The Mortality Cost of Carbon)
@Louis_Dixon performed this analysis before in a really nice post Does using the mortality cost of carbon make reducing emissions comparable with health interventions? - EA Forum (effectivealtruism.org) and found that using carbon dioxide reduction estimates from a Founder’s Pledge report:
Future pessimistic - $5.50 per tonne, so $23,400 to avert 4,255 tons*
Future realistic - $0.29 per tonne, so $1,234 to avert 4,255 tons
Future optimistic - $0.03 per tonnes, so $127 to avert 4,255 tons
The issue with your original equation above is that you are implicitly assuming linearity, i.e. assuming that the marginal cost of saving a life from marginally reducing emissions is equivalent to the average cost of saving a life if we were to reduce emissions all the way to zero. However, one of the findings of the Mortality Cost of Carbon paper is that the system is actually nonlinear and highly convex, so the number of lives saved from marginally reducing emissions is actually much greater than the average number of lives saved that you would get per ton if you were to reduce all the way to zero (see figure 4). This is all a fancy way to say that there are diminishing marginal returns in terms of saving lives from reducing carbon dioxide on a planetary scale. So to determine the marginal impact of reducing emissions, use the marginal estimates provided by the paper (the mortality cost of carbon).
And of course, as you mention above, the mortality cost of carbon is just the projected number of excess deaths from 2020-2100 caused by marginal emissions due to temperature-related mortality—i.e. the net effect of more hot days (bad for mortality) and fewer cold days (good for mortality). It leaves out potentially important climate-mortality pathways such as the effect of climate change on infectious disease, civil and interstate war, food supply, flooding, as well as the co-benefit from less air pollution. Despite these limitations, Louis was still finding that these projections were cost-competitive with Givewell’s top recommendations.
*Note that Louis was using the 2020 Working Paper version of the Mortality Cost of Carbon, which included all mortality sources from the 2014 WHO paper (one of three papers used to construct the mortality damage function, which Andrew also mentions in the post), whereas the 2021 published version of the paper in Nature Communications used just the temperature-related mortality estimates from the 2014 WHO report. This ends up leading to a slight difference in the mortality cost of carbon estimate, from 1⁄4255 in the working paper version to 1⁄4434 in the published paper version. Recalculating Louis’s analysis with the published paper version numbers yields:
Future pessimistic - $5.50 per tonne, so $24,387 to avert 4,434 tons*
Future realistic - $0.29 per tonne, so $1,286 to avert 4,434 tons
Future optimistic - $0.03 per tonnes, so $133 to avert 4,434 tons
Yes, I think it is. There is a literature on whether nuclear assistance and technology sharing for peaceful uses tends to promote or hinder nuclear proliferation, that I mention and cite a bit in my second CSIS piece.
One piece of info related to the NPT that might be helpful: The NPT does contain an article (article VI) in which the the P5 (the 5 current permanent members of the UN Security Council, who at the time the NPT was made were the only countries who had successfully tested nuclear weapons) as well as all of the parties agree to participate in good-faith negotiations to pursue nuclear disarmament, but it does not specify a time-table and the language is deliberately vague. I think the NPT has done a good job of doing what its main goal is and what its name implies: limiting nuclear proliferation. It has clearly not been able to get existing nuclear powers to get rid of all of their nuclear weapons (although it’s hard to know if the NPT has not played a significant role in reducing the arsenals of the nuclear powers relative to a counterfactual world in which there was no NPT… perhaps in a counterfactual world without the NPT, the US and USSR would not feel compelled to engage in the SALT and START negotiations without officially committing in Article VI of the NPT). Luisa has done a lot more thinking about the Nuclear Ban treaty, so I’ll defer to her on that.
Jeffrey Ohl is going to look into this question as part of a summer project for the Stanford Existential Risk Initiative, and I’ll be mentoring him. We literally just started talking about the project last week, so more to come on that! For now, I’ll say the characteristics of the technology itself that you are trying to regulate (e.g. fissile material vs. inputs to the creating of AGI for instance) is very important in terms of how a successful treaty could be constructed. This aspect is important in terms of the mechanisms that must be put in place to verify compliance with the treaty. I co-wrote an article with Chris Bakerlee on engineered pathogens for Vox a few years ago that discusses, among other things, some of the challenges around regulating biotechnology that make verifying compliance with the Biological Weapons Convention difficult https://www.vox.com/future-perfect/2018/12/6/18127430/superbugs-biotech-pathogens-biorisk-pandemic
What time range are you looking at when it comes to forecasts, and what sort of things do you have in mind? I recall when I read Superforecasting a few years ago that forecasts aren’t particularly reliable beyond a few years even for Superforecasters (though correct me if I’m wrong/maybe views on that are different now than they were then?). These treaties operate on pretty long time-scales… e.g. the NPT was conceived of in the mid 1960s, it was signed in 1968, it went into force in 1970, and then countries joined over the course of a few decades. https://en.wikipedia.org/wiki/List_of_parties_to_the_Treaty_on_the_Non-Proliferation_of_Nuclear_Weapons
One other reason why I think that understanding the NPT is important for longtermists: As the world decarbonizes to address climate change (my other big area of research), nuclear electricity generation may increase substantially into more countries, and in particular to countries with lower levels of development/technology. It’s crucial to know if the existing nonproliferation regime can ensure that this doesn’t cause proliferation, and what sorts of investments must be made to ensure that nonproliferation regime continues to work.
This is a really good point!
I think you’re right that the magnitude of the benefit from the program depends heavily on how many people end up choosing to use the mask, especially in situations where they are more likely to contract the disease. Individuals will ultimately make a personal decision based on trade-offs between the probability of contracting the virus, comfort, convenience, and even fashion.
I also think there is significant heterogeneity in terms of how people weigh these factors. I do think that there are a significant number of people who, net of these factors, would decide that the benefits of wearing a medical-grade respirator in situations where they are more likely to contract the virus outweighs the costs. These could be seniors, people with preexisting conditions, people who don’t find the respirator uncomfortable, or people who are just risk averse.
I also think that there are currently significant numbers of people who would like to wear medical-grade respirators, but who are not currently able to get them. I have friends that are teachers that are required to teach in person that want a medical-grade respirator, but are not able to get one. As I noted above, there is still a shortage of respirators even for frontline medical workers (see https://www.washingtonpost.com/business/scarcity-of-raw-material-still-squeezes-n95-mask-makers/2020/09/10/94586834-f31e-11ea-8025-5d3489768ac8_story.html). I think there are probably enough people in this category, that you could make some dent in the infection rate with this policy, though how much depends on people’s behavior.
Also, one of the general takeaways is that, even if the benefits end up being modest (e.g. you reduce the infection rate, but not below 1 in all areas), the relative cost is so cheap that I think it’s worth it to give it a shot.
A few other points:
-As part of the program, it would be great to do randomized control trials with different types of respirators (e.g. different designs that meet the N-95 standard, enhanced N-99 or N-100 designs). There may be some sort of trade-off between comfort and protection (granted that the N-95 threshold is met), and perhaps going more on the side of comfort is optimal because the benefit from higher compliance outweighs the slightly lower protection. There may also be an N-95 design that is already produced (or gets produced for the program) that is just more comfortable and gets higher compliance, and we’d be able to figure that out. That face shield you mentioned is really cool! You could also pilot something like that as part of this program, and perhaps that wins out.
-Along these lines, I also considered adding another point, which would be creating a program called the “N-95 for all Studio,” where fashion designers or people like that could add designs to the respirators to make them look cool. You could imagine charging someone $2 or something to get the “New York Yankees N-95″ or the “Tom Ford N-95” or whatever.
-Also as winter comes in the Northern Hemisphere and as more activity moves inside and the ability to ventilate rooms goes down, there will likely be more spaces with a higher concentration of aerosols. The benefit of wearing a respirator vs. cloth mask or surgical mask goes up in this situation, so this would affect people’s behavior.
-I’d also emphasize the benefits of this policy for preparing for future pandemics. It so happens that SARS-COV-2 has a case fatality rate ~1%, and this is quite heterogeneous depending on your age and existing health. If there is a respiratory-transmitted pandemic that has a 30% case fatality rate, then the benefits of wearing a respirator will be way higher versus the costs from inconvenience, discomfort, etc.
What I had in mind with this policy was that the government would contract directly with producers (using the defense production act where necessary) to procure enough N-95 respirators for everyone in the country, and the government would then distribute them to everyone. There would be some agreed upon price of procurement between the government and manufacturers that would be negotiated at the start of the process. If manufacturers want to produce more respirators than what they contracted for, they are welcome to do that and to sell it at a price they choose.
What I mean by cannot buy is that N-95s are unavailable to nearly all people who may want to purchase them https://twitter.com/davidrliu/status/1319980228765274112?s=20. I’ve looked online throughout the pandemic, and they are usually unavailable for purchase. Sometimes, you can add them to your cart, but then you can’t check out because you get a warning that they are being prioritized for frontline workers (that screenshot above is me doing exactly that). Sometimes, you can buy more heavy duty P100 respirators that have traditionally been used for doing something like spray painting, but a lot of people prefer not to wear those regularly because they are more bulky.
Thanks, John! I really like your distinction between the type (1) and type (2) “pernicious moral hazard.”
Yes I agree that the moral hazard I mention here would not be large enough to outweigh the benefits of the policy, putting it in the category of (1). My goal in that “potential issues” section was to think about the universe of potential issues that people could raise about the policy and address them. As you can tell, I don’t currently think any of the issues are significant enough to make the policy not worth it.
By the title, I thought this was going to be a discussion of the dangers of appeasing genocidal dictators (e.g. https://www.ynetnews.com/articles/0,7340,L-3476200,00.html) … clearly I was wrong!
FYI, I gave a presentation on my Mortality Cost of Carbon paper at the UCLA Climate Adaptation conference two days ago, available here: https://event.on24.com/wcc/r/2688287/118B1E2E57B33A902FDE6CE95202DB34 This is a brief (~20 minutes) less technical overview of the paper. My presentation starts at 53:20.
Also, the other two speakers on the panel (Tamma Carleton and Ishan Nath) were both authors on the Climate Impact Lab paper that Louis had posted about earlier: https://forum.effectivealtruism.org/posts/PATHShQoxQLHoZ7rE/linkpost-global-death-rate-from-rising-temperatures-to
My Mortality Cost of Carbon working paper is here: https://ceep.columbia.edu/sites/default/files/content/papers/n11.pdf
- Cost Effectiveness of Climate Change Interventions by (16 Feb 2022 2:58 UTC; 23 points)
- 's comment on Cost Effectiveness of Climate Change Interventions by (16 Feb 2022 17:29 UTC; 19 points)
- The DICE-2023 model of the Social Cost of Carbon has revised up the harms of climate change, and down the costs. At what point does climate change become cost competitive with global poverty charities? by (14 Apr 2023 17:22 UTC; 19 points)
FYI, Michael Greenstone (one of the authors of this study, the co-director of the Climate Impact Lab, and the Milton Friedman Distinguished Service Professor in Economics at University of Chicago) testified at a hearing in Congress on the health impacts of climate change a few weeks ago: https://youtu.be/N8nCZC0_yxU His opening statement is available in written form here: http://www.impactlab.org/news-insights/michael-greenstone-testifies-on-the-health-impacts-of-climate-change/
The copy you have is their 2019 version of the paper. The figure 9 I am referring to is their most recent 2020 NBER Working Paper version of the paper linked in the original post.
I agree that the RCPs, which were made in 2011, are outdated at this point. This is in large part because of the strong performance of renewable energy over the last decade. The RCPs at this point are still the standard emissions scenarios that are used in scientific papers, although I expect them to be updated in the near future when the next IPCC report comes out. Somewhere between RCP 6.0 (~3.2 degrees C in 2100) and RCP 8.5 (~4.8 degrees C) is probably what you can call a baseline emissions scenario (source: http://live.magicc.org/). The baseline emissions scenario in DICE-2016 for instance—which involves significant reduction in emissions per unit of GDP, continued economic growth, and a small amount of carbon emissions abatement—results in 4.1 degrees C warming in 2100. Still, the Climate Impact Lab results are pretty significant in any of these scenarios as you can see in figure 9a. In RCP 8.5, you get to 3.2 degrees C in about 2065 and you get to 4.1 degrees C around 2085. At both of those dates, there are significant increases in mortality. Just eyballing it, it looks like ~1/2 and ~4/5 of the mortality increase at 4.8 degrees C in 2100 respectively.
Also, if you wanted to look at the net mortality effect of a high emissions scenario with a lot of coal burning, you would also need to consider the effect of this on particulate matter pollution in addition to the affect from changing the climate. The particulate matter effect is very large and the climate impact paper does not account for this. This paper, for instance, does: https://www.nature.com/articles/s41467-019-09499-x/tables/2.
For the mitigating effect of income on mortality, I’d emphasize that there is significant uncertainty in these projections as shown in figure 9b, in large part driven by uncertainty around adaptation. For instance, with 80% confidence, they can’t rule out the mortality effect of climate change being on net positive. Though from the perspective of decision theory, if you have a lottery across the possible outcomes in 2100 that include both sanguine and higher than expected damages and you have risk aversion (which most people do), this would cause you to want to undertake stricter climate policy than if you just look at the central estimate. I’d also emphasize that this is a very active area of research (e.g. this conference is happening next month: https://climateadaptationresearch.com/agenda/) so we will continue to get better at estimating climate impacts net of adaptation.
Hi Rhys, thanks for the question! Currently, this is just a proposal, and there is no one that I know of who is working on implementing it. But I hope that sharing the idea is useful to folks who may be interested in pursuing the idea or related ideas! Folks should reach out to me if they are interested in pursuing this idea (or taking some nugget of it to inform other ideas)!
In similarly structured organizations, e.g., the IPCC, there are PhD researchers who are involved as chapter authors (I have a few friends from my PhD program who are IPCC authors). However, the more senior positions (e.g., chapter lead authors) tend to be more senior folks.