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comment by AGB · 2019-09-10T20:44:54.094Z · score: 39 (19 votes) · EA · GW
If a climate change intervention has a cost-effectiveness of $417 / X per tonne of CO2 averted, then it is X times as effective as cash-transfers.

Wait a second.

I'm very confused by this sentence. Suppose, for the sake of argument, that all the impacts of emitting a tonne of CO2 are on people about as rich as present-day Americans, i.e. emitting a tonne of CO2 now causes people of that level of wealth to lose $417 at some point in the future. There is then no income adjustment necessary (I assume everything is being converted to something like present-day USD for present-day Americans, but I'm not actually sure and following the links didn't shed any light), so the post-income-adjustment number is still $417. Also suppose for the sake of argument that we can prevent this for $100.

This seems clearly worse than cash transfers to me under usual assumptions about log income being a reasonable approximation to wellbeing (as described in your first appendix), since we are effectively getting a 4.17x multiplier rather than a 50-100x multiplier. Yet the equation in the quote claims it is 4.17x more effective than cash transfers*.

What am I missing?

*Mathematically, I think the equation works iff. the cash transfers in question are to people of comparable wealth to whatever baseline is being used to come up with the $417 figure. So if the baseline is modern-day Americans, that equation calculates how much better it is to avert CO2 emissions than to transfer cash to modern-day Americans.

comment by StevenKaas · 2019-09-10T20:59:21.773Z · score: 24 (12 votes) · EA · GW

I was about to say this and then saw your comment. My impression from the paper is the $417 is a sum of costs to different countries, and for each of them the cost is a present value to the people in that country, with discounting being applied based on the expected amount of economic growth in that country. So I don't think it's calibrated to present-day Americans, but I don't think it's calibrated to the world's poorest either, and I agree the argument doesn't go through.

There's another problem with the quoted claim, which becomes clear if you pick a value like X = 1/1000. Paying $417,000 to avert a tonne of carbon is a huge net bad and not just a much smaller net good.

It seems to me another problem is that if the social cost of carbon comes from effects on growth, you have to compare that to the effects on growth of cash transfers. It's generally easy for small changes in growth rate to outweigh small changes to level in the long run, so if you compare the growth effects of one intervention to the level effects of another intervention, it's no surprise that the former would seem more effective.

comment by Robert_Wiblin · 2019-09-13T13:47:42.924Z · score: 10 (6 votes) · EA · GW

Am I right that what we need to know is whether, when assessing the total global social cost of carbon:

i) they multiplied harms to the world's poorest people, measured in equivalent dollars of their income, by ~100x;

ii) they divided the harms to the world richest people, measured in equivalent dollars of their income, by ~100x;

iii) or something in between?

HH's argument only goes through if it's the second of the three.

comment by AGB · 2019-09-13T14:07:36.855Z · score: 5 (3 votes) · EA · GW

I agree with this. I would have assumed they would do (i), and other responses from people who actually read the paper make me think it might effectively be (iii). I don't think it's (ii).

comment by cole_haus · 2019-09-13T20:27:41.473Z · score: 1 (1 votes) · EA · GW

I mentioned it in my comment elsewhere, but—from a quick look at the paper and the supplementary material—I don't think it's much like any of these. They don't make any special mention that I could find of trying to translate purely economic measures into welfare. The only mention I could find about income adjustment is "rich/poor specifications" which appears to be about splitting the formula for growth of damages into one of two forms depending on whether the country is rich or poor.

More plainly, I think the final number should be interpreted as yet another estimate in the long line of social cost of carbon estimates. It seems to be measuring the same thing as all the others (i.e. not utility) and I don't know where the idea of income-adjustment in this post is coming from.

comment by StevenKaas · 2019-09-13T19:06:50.634Z · score: 1 (1 votes) · EA · GW

My nonconfident best guess at an interpretation is that, according to these estimates, for every tonne of carbon:

Future Indians suffer damages utility-equivalent to the present population of India paying a total of $76

Future Americans suffer damages utility-equivalent to the present population of the USA paying a total of $48

Future Saudis suffer damages utility-equivalent to the present population of Saudi Arabia paying a total of $47

Next are China, Brazil, and the UAE, all with $24, and then a lot of other countries, and the sum of all these numbers is $417. So it's as if the $417 is paid by this particular mix of the world's people, making it iii), something in between. These numbers are totals that don't divide by population, so an individual inhabitant of Saudi Arabia or the UAE pays a greater absolute amount than an individual American, who pays a greater absolute amount (but a smaller percentage of income) than an individual Indian.

comment by DannyBressler · 2019-09-10T16:55:25.886Z · score: 22 (9 votes) · EA · GW

Below is one important point that I think is extremely difficult to know without being an active researcher in the field. Hauke hints at it in his footnote 6, but I want to expand on it since I think it is important to understand where the social cost of carbon estimates are coming from:

Ricke et al. 2018 (https://www.nature.com/articles/s41558-018-0282-y) are using a climate damage function that predicts much higher damages than the damage function that is used in the main integrated assessment models (IAMs) that predict the social cost of carbon (DICE, FUND, and PAGE). (I've included a note with links on this below for those who are interested). This results in an important point:

Most of the difference in the social cost of carbon between Ricke et al. 2018 and the main IAMs is because they are using different damage functions, not because they are accounting for greater marginal utility of consumption to individuals with lower consumption levels.

The more appropriate control would be to compare Ricke et al. 2018 to the gro-DICE model developed by Diaz & Moore 2017 ( https://www.nature.com/articles/nclimate2481 ), which uses a damage function that is more similar to Ricke et al. 2018. gro-DICE projects a social cost of carbon of $220, compared to Ricke et al.'s $415. However, the gro-DICE damage function is still less damaging than Ricke et al's damage function. Ideally, we would want to do a comparison of the social cost of carbon using the same damage function (so we could isolate just the effect of differences in marginal utility), but unfortunately we can't readily do this because these papers are all using different damage functions. Given that Ricke et al. are using the most damaging damage function, we do know that the effect would be less.


Note on climate damage functions: Ricke et al. 2018 use a damage function based off of Burke, Hsiang, and Miguel 2015 ( https://www.nature.com/articles/nature15725 ). This is the "most damaging" of the damage functions in the literature. Diaz & More 2017 uses a damage function based on Dell, Jones, and Olken 2012 ( https://www.aeaweb.org/articles?id=10.1257/mac.4.3.66), which is more damaging than the damage functions used in traditional IAMs, but not as damaging as the Burke, Hsiang, and Miguel 2015 damage function used in Ricke. et al. 2018.

These analyses predict much higher climate damages than the analysis that make up the DICE-2016 damage function (the DICE-2016 damage function is derived here: https://cowles.yale.edu/sites/default/files/files/pub/d20/d2096.pdf ). The reason for this is differences in econometric strategy, which is often called the "levels vs. growth debate." See Auffhamer 2018 ( https://www.aeaweb.org/articles?id=10.1257/jep.32.4.33 ) for a nice discussion of the reason why these vary. In general, this is an active debate in the field and there is not consensus on the appropriate way to predict economic damages from climate. 2018 Nobel winner William Nordhaus, for instance, would fall in the "levels" camp, and young superstar researchers Solomon Hsiang from Berkeley and Marshall Burke from Stanford would fall in the "growth" camp.

comment by jackva · 2019-09-11T21:06:49.479Z · score: 14 (5 votes) · EA · GW

Very interesting.

In my experience the debate about climate damage is quite ideologically loaded so I am a priori very skeptical of using a single study for these kind of estimates, they always come with a host of assumptions that are ultimately fairly arbitrary.

In addition when you have a causal chain of at least three steps (climate sensitivity > impact of warming > human response) each with significant uncertainty that affects the next step it seems easy to get the estimate wrong by much more than one order of magnitude so the strategy of saying 'even if we take a tenth of the estimate' to save us from overestimation does not seem sufficient to me.

comment by Halstead · 2019-09-12T10:22:59.843Z · score: 12 (5 votes) · EA · GW

I would agree with this. My understanding is that the IAMs are so unmoored from reality as to be basically useless. They don't try to account for the risk of catastrophic impacts, and the damage functions are chosen in part for mathematical tractability rather than fidelity to what climate change will actually be like. This is why I would object to claims such as "new research shows that the social cost of carbon is $477".

This also seems like an area in which expert elicitation won't be very accurate. We're talking about impacts 100 years into the future for a problem heavily dependent on political developments which are extremely difficult to predict.


comment by cole_haus · 2019-09-10T21:03:16.594Z · score: 3 (3 votes) · EA · GW

Thanks, this is interesting! I quickly read through the core paper and am a bit confused.

It seems like you're understanding income adjustment to be one of the main additions in the paper. Where are you seeing that? The title/abstract/etc. seem to be pitching greater spatial resolution as the main contribution. Greater spatial resolution helps with income adjustment but isn't sufficient. As far as I can tell the paper primarily uses regular old GDP per capita (with the de rigeur acknowledgement that GDP isn't a great welfare measure). The only income adjustment I see is a couple of mentions of rich/poor specifications and the supplementary information suggests that this is just splitting the formula for the growth of damages based on whether a country falls into the rich bin or poor bin.

They explain the increased cost not as due to income adjustment (as I understand things) but because:

The median estimates of the GSCC (Fig. 1) are significantly higher than the Inter-agency Working Group estimates, primarily due to the higher damages associated with the empirical macroeconomic production function

All that said, I wish it did use logarithmic utility because that seems like an important improvement!

(FYI: All the inline footnotes still link to a Google doc.)

comment by Wayne_Chang · 2019-09-14T04:32:24.035Z · score: 1 (1 votes) · EA · GW

Hauke's calculation simply determines a standard Benefit/Cost ratio. If it costs $10 to avert a tonne of CO2 that provides benefits of $417 (in damages averted), this Benefit/Cost ratio equals 41.7. This ratio should be directly comparable to Copenhagen Consensus 'Social, economic, and environmental benefit per $1 spent.' For the Post-2015 Consensus, 'Climate Change Adaption' is listed as providing a Benefit/Cost ratio of 2 while climate-related 'Energy Research' has a ratio of 11. I would weight these results from meta-level research must more strongly than that from a single study. But even if we believed Hauke's study, a benefit/cost ratio of 41.7 still lags 'Reduce Child Malnutrition' (ratio of 45) or 'Expanded Immunization' (ratio of 60). This hardly suggests that "we should consider prioritizing climate change over global development interventions." The unconditional cash transfer benchmark that Hauke uses is a minimum and not representative of highly cost-effective interventions in global development. Using GiveWell's estimates, deworming and malaria nets are more than 10x more cost-effective than cash. Before rushing to replace well-established priorities and interventions that are based on decades of research, we need to have substantial confidence in the new priority/intervention. This study is far from it.

Note that the Copenhagen Consensus and GiveWell results do not apply utility adjustments. If this new climate change study does so, its Benefit/Cost ratio would be distorted by improperly inflating Benefits, which make the ratio larger than it actually is.

comment by RomeoStevens · 2019-09-10T20:23:29.267Z · score: 1 (1 votes) · EA · GW

This is really interesting. I'm curious about crowding out and marginal dollar effects. i.e. the smart money spends all its resources on this, allowing the dumb money to free ride and keep on with the status quo (or even get worse with less perceived consequences). Meanwhile, there are now far less smart dollars available to fund weird moonshots that only the smart money can think about.

One solution: more funding for geoengineering moonshots (and please, with fewer assumptions that geoengineering automatically means that safety and reversibility aren't major design criteria).