This is really good! I’m glad to see such a transparent, well-designed writeup on the state of climate change and technology in 2019, and I especially liked the importance // neglectedness // tractability table. I was also surprised to see how little philanthropists currently spend in this area (especially given the large number of very wealthy people who are concerned about climate change).
A couple of parts that confused me:
ITIF has a track record of influential policy research with the potential for policy change. For instance, in 2016, ITIF’s Robert Atkinson and Michael Lind were granted $155,000 to “research and write a book that reviews and synthesizes existing research on what firms of different sizes contribute to the economy”. In 2018, this book was published by MIT Press and reviewed in the New York Times. This leads us to believe that ITIF could really change the conversation on climate change policy towards increased focus on clean energy innovation policy.
This example doesn’t seem to have anything to do with “the potential for policy change”. Getting a grant and writing a book are both accomplishments, but what evidence is there to show that ITIF is unusually good at driving change? Is their being voted as the best think tank in their domain based on relevant researchers’ views on their success?
Also, on your Fermi estimate: The table presents numbers in the form “if $X in donations increases R&D spending by $Y, the benefit is $(Y—X).” I wish it also presented some estimate for the expected climate impact of increased R&D spending. That figure may be somewhere on the site, but I didn’t find it in a quick read-through, and it feels like we never get around to calculating an actual impact estimate that can be compared to the many other donation opportunities we have. Is spending $2 million to generate $50 million in R&D likely to produce more good for human life than buying 400,000 mosquito nets? Maybe yes, maybe not, but I’m not sure how to figure out the range of possible answers.
Thank you so much for your excellent comments—there seems to be a theme in there that captures something interesting about the way people in EA think.
>>This example doesn’t seem to have anything to do with “the potential for policy change”.
I see what you’re saying: my example is definitely not decisive evidence for a strong causal links between ITIF’s policy research and policy change. But I feel that saying that this example doesn’t have anything to do with the potential for policy change is a bit strong. Under Obama, if you wanted to get right people talking about an issue then publishing a book at MIT press and having it reviewed in the NYT seems like a good start. I have added a statement about that the book was launched at an event at the National Press Club with Financial Times Washington commentator Edward Luce.
But yes this was just one point, for instance, elsewhere in the report we write “The launch event for this report demonstrated that ITIF had good convening power, with high-profile panelists such as a former deputy head of the US Environmental Protection Agency.[44] “
And yes ITIF is a very well regarded think tank based on the top rankings on the global think tank rankings. Think tanks are generally meant to change policy and so a good ranking is likely to indicate this. This is more of a holistic argument (cluster thinking if you will).
Relatedly and re: your comment on the Fermi estimate:
In the report I write (I’ve made some minor changes now to make this more clear).
“What effect will the spending increases have on clean energy costs? Above we cited a meta-analysis of studies surveying experts suggesting that energy costs will decrease by several percentage points, if energy R&D is increased from a low to a medium or high investment scenario. The table below shows how many additional million dollars in clean energy R&D the low, medium and high investment scenarios correspond to. The amount of increase for some of the medium scenarios are roughly the same order of magnitude as benefits under realistic and optimistic assumptions in our cost-effectiveness analysis ($53 million and $750 million; see Table 2) and so this project could plausibly decrease low carbon energy costs significantly.
As mentioned above, because World Energy expenditure is in the trillions, [48],[49] even a small reduction in cost by several percentage point might lead to large savings. This cost-effectiveness analysis is roughly in line with a recent study which found that combining clean energy innovation with emission reduction policies reduces the costs of climate mitigation with a net present value of $3-6 trillion.[50]”
>>Is spending $2 million to generate $50 million in R&D likely to produce more good for human life than buying 400,000 mosquito nets? Maybe yes, maybe not, but I’m not sure how to figure out the range of possible answers.
One could multiply things out further if one feels inclined to, but the model uncertainty increases so much that it doesn’t allow for meaningful comparison with other causes.
This is more of a high risk, high reward donation opportunity than the low risk, low reward global development interventions whose benefits are more readily quantifiable and comparable. I think it’s definitely much better in expectation—I’d rather have a reasonable chance of lowering carbon electricity prices by a few percent than save 40 lives with 400,000 bednets.
I think we need to be careful of precision bias in EA and favouring ever more elaborate, explicit cost-effectiveness modelling of low risk easily quantifiable interventions while neglecting the more high risk “better approximately right than precisely wrong” kind of interventions.
I agree though that it’s hard to say whether this is better than funding say policy reform that would improve trade with emerging economies or biosecurity.
Yes, we should clearly aim to avoid precision bias. I don’t actually make donation decisions using comparisons of this kind—I just wanted to point out what I saw as a lack of clear “final benefit” description along the lines of “assuming a middling outcome, we’d expect to prevent roughly X tons of carbon/Y degrees of warning”.
But I wouldn’t be surprised if some figure like that was embedded in the report and I just couldn’t easily find it.
--
Also, it took me a while to find the section where the report explained potential reasons behind the (apparently) drastic undersupply of R&D funding: Here’s the explanation, which helped me get a better handle on why this cause has such high potential impact numbers behind it.
Have you spoken to Open Phil about this opportunity? Are you aware of any research they’ve done into R&D funding, or R&D policy grants they’ve made? It seems like this would fit under their “transformative basic science” or “global catastrophic risk” portfolios, and they’ve previously made at least one speculative grant with a small chance of sharply reducing emissions.
>>what I saw as a lack of clear “final benefit” description along the lines of “assuming a middling outcome, we’d expect to prevent”.
I think a thorough “final benefit” / “$ per ton of CO2 equivalent”/ “$ per degree of warming averted” calculation is not in principal outside of the realm of empirical investigation, but there are many difficulties here (e.g. the elasticity of clean energy demand, the comparative carbon intensities of other low carbon energy etc.). I might come back to that in case there is very strong demand for these numbers. But I also don’t think we need these calculations for the same reason that many high risks, high return grants lauded in the EA community do not need to include a “$ per life saved” calculation. I do have a bunch of what Bostrom calls crucial considerations in this report and I think EA research should head perhaps more in that direction.
But for what it’s worth we do mention the economic benefits of reducing global low carbon energy costs by several percentage points. They might be very large, because World Energy expenditure is in the trillions, [48],[49] and even a small reduction in cost by several percentage point might lead to large savings. Also there is a recent study which found that combining clean energy innovation with emission reduction policies reduces the costs of climate mitigation with a net present value of $3-6 trillion.[50]
Also, one economic model suggests that “if a carbon tax imposes a dollar of cost on the economy, induced innovation will end up reducing that cost to around 70 cents”.[73] Given that political acceptability is mainly a function of cost, making clean energy cheaper might make carbon taxes more likely. Just based only on this effect, it might make this a really good reason for donating to this, but again it’s hard to quantify the exact benefits.
>>Have you spoken to Open Phil about this opportunity?
I do not know OpenPhil’s official position on this, but there is a cell in “Open Philanthropy Project’s Public Priorities- Global Catastrophic Risks” spreadsheet which mentions that clean tech R&D might be a potential philanthropic opportunity. But the same spreadsheet also mentions says that Anthropogenic climate change (other than geoengineering) is not prioritized. I’ll definitely approach them though.
Just picking up on the importance, neglectedness, tractability table, Hauke, can I ask you to explain what you meant by those three terms (or, at least the last two) and how you see them as fitting together to give you an estimate of cost-effectiveness? I notice you did a fermi estimate too, so can you say what the relationship is between I, N, T and the fermi estimate? This isn’t a critical question—I’ve been thinking about cause prio a lot and I’ve realised it’s not clear to me how people use these concepts in their decision-making. Hence, if you could say a bit more that would helpful.
As suggestions:
is tractability: cost-effectiveness, resources requires to solve the problem, subjectively-perceived easiness, or something else?
Is neglectedness: resources going towards the problem? if so, how directly targeted at the problem did you have mind? Is it about counterfactual replacability? Something else?
Is the idea I, N, and T somehow give you an intuitive cost-effectiveness estimate and then you build the fermi estimate as an explicit follow up?
Sorry if this seems pedantic and I’m not engaging with the spirit of your post. The research looks very thorough and I’m glad you did it. As a non-expert on the subject matter I probably don’t have much of substance of add to that.
My understanding of these terms is roughly as follows:
Scale: general size of the problem. Determines the upper bound of what can be achieved. Determining the scale of a problem is quite arbitrary, because how do you draw the boundaries of ‘the problem’ and when is it completely solved?
Tractability: determines the average or global cost-effectiveness if you don’t know where you are on the curve (i.e. if you don’t know how much of the problem has been solved so far). Higher tractability means that the curve is steeper on average.
Neglectedness: determines the location on the curve and gets you the marginal or local cost-effectiveness. Because we expect the value curve to have diminishing returns, a good heuristic is ‘more neglected --> higher marginal value.’
I think where EA’s go repeatedly wrong with the application of the model is that tractability and neglectedness get confused: tractability should refer to solving the complete problem. If it refers to marginal tractability, then it double counts the neglectedness consideration. The report seems to do this:
Public clean energy R&D is neglected: only $22 billion is spent per year globally. Many advanced economies such as the US could unilaterally increase this substantially i.e. even without international coordination—which makes this policy uniquely politically tractable.
Here, neglectedness is taken as a reason for tractability, while it should be a reason for marginal cost-effectiveness.
The SNT-model is also much more helpful for funding than for career choice, because neglectedness has linear implications for the value of extra funding, but more complex implications for an extra person doing work. Some skills are not very useful in the early stage of a cause area or problem, but become valuable only later. In general, I think personal fit is very important, and the SNT-model does not account for it.
I actually hope to write a longer post explaining all this in more detail, including some nice visual explanation I have of the SNT-model.
Here, neglectedness is taken as a reason for tractability, while it should be a reason for marginal cost-effectiveness.
No sorry that’s incorrect. These are two separate points.
Clean energy R&D is neglected because only $22 billion globannually are invested—Norway could in theory triple this if they wanted to and it would have a very large effect on global emissions.
Carbon taxes are also neglected. But if Norway were to implement a carbon tax the effect on global emissions would be tiny.
Increasing public clean energy R&D does not necessarily require strong multilateralism or harmonized national policies. This makes it very tractable politically and uniquely positioned in the space of all climate policies as a decentralized approach.
Even if clean energy R&D spending would be relatively higher (say 100 billion), it might still be more tractable for a small country to increase it than to implementing carbon taxes.
Ah, I assumed the latter was a consequence of the former because they were in the same paragraph, my bad.
However, like Michael, I’m still a bit confused about the role neglectedness is playing in this analysis (and all other analyses). But don’t take that as criticism of your analysis. It often seems that neglectedness and tractability (and scale) are used as independent reasons to support a particular cause area or intervention, rather than that they are used as a coherent framework. It seems to me your argument would have been similarly strong if clean energy R&D was not neglected—if you could just show that additional spending would have big benefits.
I do not have a super strict definition of the ITN framework, but we are inspired by 80k’s ITN methodology. The arguments and findings from the ITN analysis, sometimes serve as inputs to the fermi estimate.
Tractability for instance we mention several times throughout the report:
“Public clean energy R&D is neglected: only $22 billion is spent per year globally. Many advanced economies such as the US could unilaterally increase this substantially i.e. even without international coordination—which makes this policy uniquely politically tractable. ”
“Increasing public clean energy R&D does not necessarily require strong multilateralism or harmonized national policies. This makes it very tractable politically and uniquely positioned in the space of all climate policies as a decentralized approach (see Figure 4).”
Or:
“Political tractability of carbon pricing approaches
Carbon pricing is becoming increasingly unpopular and politically difficult to implement.[173] One commentator writes that “the carbon tax’s fading appeal, even among groups that like it in principle, shows the difficulties of crafting a politically palatable solution to one of the world’s most urgent problems”.[174] It might be an even larger political challenge to increase the carbon tax to reflect the social cost of carbon (i.e. the true price of the externalities).[175] The political feasibility of a carbon tax is further decreased by the seemingly endless debates on how high it be should be (although it would make sense to set the carbon price to the marginal abatement cost, which is easier to estimate than the marginal social cost of carbon,[176] or use the lower bound of the social cost of carbon,[177] and/or simply err on the side of overestimating externalities, while reducing other non-Pigovian taxes).
On the positive side, carbon pricing might face less industry pushback and regulatory capture than many might assume: Major fossil fuel companies are advocating for carbon pricing.[178] This might be a case of ‘Bootleggers and Baptists,’[179] a phenomenon in which profit-driven corporations cause externalities (bootleggers) to align politically with socially motivated governments (baptists) trying to reduce externalities, as pushing for tighter regulation of their own industry (e.g. alcohol, carbon) gives them an advantage by making it harder for new competition to enter the market. On the other hand, the fossil fuel companies have invested over $1 billion on misleading climate-related branding and lobbying.[180]
In the appendix, we list two different ways of measuring national efforts to price carbon. The first is the country’s environmentally-related tax revenue as a percentage of GDP (e.g. gas taxes etc.). The second measure takes into account both carbon taxes and emission trading systems to calculate the effective carbon rate.”
“Cheaper clean energy technology might save the world a lot of money and might reduce both emissions and poverty. Many people also suggest that this would make a carbon tax more politically palatable.”
“Theoretically, a perfect global carbon pricing regime implemented early might have been the only policy needed to prevent climate change.[143] Leading economists agree that carbon taxes are a great policy intervention.[144] Increasingly, advanced economies do price or tax carbon emissions. A global carbon price would lead to lower emissions and incentivize the private market to build cleaner energy technology. Although there are proposals and increasing public support for a global carbon tax,[145] the biggest challenge still is that they do not seem politically palatable enough.[146] Some countries, such as Russia, derive a substantial part of their GDP from fossil fuels[147] and it might thus be in their interest not to adopt a carbon price.”
On neglectedness:
“Public clean energy R&D is neglected: only $22 billion is spent per year globally compared to $140 billion spent on clean energy deployment subsidies and trillions spent on energy.”
“But is public spending on clean energy R&D really neglected? Is it effective to spend more? We think so. Consider that, globally, only $22 billion in public funds are spent on clean energy R&D annually—this is only 0.02% of World GDP.[18] For comparison, world energy expenditure was 6% of the World’s GDP. This means we spend about 300 times as much on energy than on making energy better.
Why is there so little investment in clean energy innovation?
Generally, basic R&D is under-supplied at both the private and public level. There are several theoretical reasons for this:
On a global level, basic clean energy R&D is under-supplied by both governments and the private sector. Why? Because it suffers from the free-rider problem, as all basic R&D and public goods do. Countries and firms can just let others do the basic research and then reap the benefits because knowledge is hard to protect internationally. Private R&D cannot be protected perfectly because patents expire or industry know-how diffuses to other firms and not all rents from investments can be captured. This results in a socially suboptimal investment. In other words, additional public investment through basic R&D funding and subsidies increase social surplus, because private capital can only capture a fraction of the social surplus pie.
Generally, venture capital and the market neglect capital-intensive, high-risk, high-return, long time-horizon investments.
Clean energy R&D, in particular, is under-supplied because externalities of carbon are not priced adequately, leading to insufficient commercial applications for clean energy R&D.”
“First, generally,clean energy innovation is neglected by philanthropists. US philanthropists gave only $115,000 in grants to promote government clean energy R&D spending and only $20,000 to promote the role of government in fostering innovation annually on average from 2011-2015.[52] This suggests that there are likely still increasing returns to scale.”
“Climatechangeis relatively non-neglected
Climate change is a high-profile topic that many people work on. It is funded by both governments and big private foundations. Thus, even though clean energy innovation in particular has been relatively underfunded within the climate policy space, it is conceivable that in the future ITIF might receive grants for their clean energy innovation program from other funders, which lowers the counterfactual impact of donating to this project. In other words, comparatively, climate change is not very neglected. For instance, the risks and expected losses of pandemics are of a similar magnitude than those of climate change, yet the area is more neglected by other funders.[75]”
This is really good! I’m glad to see such a transparent, well-designed writeup on the state of climate change and technology in 2019, and I especially liked the importance // neglectedness // tractability table. I was also surprised to see how little philanthropists currently spend in this area (especially given the large number of very wealthy people who are concerned about climate change).
A couple of parts that confused me:
This example doesn’t seem to have anything to do with “the potential for policy change”. Getting a grant and writing a book are both accomplishments, but what evidence is there to show that ITIF is unusually good at driving change? Is their being voted as the best think tank in their domain based on relevant researchers’ views on their success?
Also, on your Fermi estimate: The table presents numbers in the form “if $X in donations increases R&D spending by $Y, the benefit is $(Y—X).” I wish it also presented some estimate for the expected climate impact of increased R&D spending. That figure may be somewhere on the site, but I didn’t find it in a quick read-through, and it feels like we never get around to calculating an actual impact estimate that can be compared to the many other donation opportunities we have. Is spending $2 million to generate $50 million in R&D likely to produce more good for human life than buying 400,000 mosquito nets? Maybe yes, maybe not, but I’m not sure how to figure out the range of possible answers.
Thank you so much for your excellent comments—there seems to be a theme in there that captures something interesting about the way people in EA think.
>>This example doesn’t seem to have anything to do with “the potential for policy change”.
I see what you’re saying: my example is definitely not decisive evidence for a strong causal links between ITIF’s policy research and policy change. But I feel that saying that this example doesn’t have anything to do with the potential for policy change is a bit strong. Under Obama, if you wanted to get right people talking about an issue then publishing a book at MIT press and having it reviewed in the NYT seems like a good start. I have added a statement about that the book was launched at an event at the National Press Club with Financial Times Washington commentator Edward Luce.
But yes this was just one point, for instance, elsewhere in the report we write “The launch event for this report demonstrated that ITIF had good convening power, with high-profile panelists such as a former deputy head of the US Environmental Protection Agency.[44] “
And yes ITIF is a very well regarded think tank based on the top rankings on the global think tank rankings. Think tanks are generally meant to change policy and so a good ranking is likely to indicate this. This is more of a holistic argument (cluster thinking if you will).
Relatedly and re: your comment on the Fermi estimate:
In the report I write (I’ve made some minor changes now to make this more clear).
“What effect will the spending increases have on clean energy costs? Above we cited a meta-analysis of studies surveying experts suggesting that energy costs will decrease by several percentage points, if energy R&D is increased from a low to a medium or high investment scenario. The table below shows how many additional million dollars in clean energy R&D the low, medium and high investment scenarios correspond to. The amount of increase for some of the medium scenarios are roughly the same order of magnitude as benefits under realistic and optimistic assumptions in our cost-effectiveness analysis ($53 million and $750 million; see Table 2) and so this project could plausibly decrease low carbon energy costs significantly.
As mentioned above, because World Energy expenditure is in the trillions, [48],[49] even a small reduction in cost by several percentage point might lead to large savings. This cost-effectiveness analysis is roughly in line with a recent study which found that combining clean energy innovation with emission reduction policies reduces the costs of climate mitigation with a net present value of $3-6 trillion.[50]”
>>Is spending $2 million to generate $50 million in R&D likely to produce more good for human life than buying 400,000 mosquito nets? Maybe yes, maybe not, but I’m not sure how to figure out the range of possible answers.
One could multiply things out further if one feels inclined to, but the model uncertainty increases so much that it doesn’t allow for meaningful comparison with other causes.
This is more of a high risk, high reward donation opportunity than the low risk, low reward global development interventions whose benefits are more readily quantifiable and comparable. I think it’s definitely much better in expectation—I’d rather have a reasonable chance of lowering carbon electricity prices by a few percent than save 40 lives with 400,000 bednets.
I think we need to be careful of precision bias in EA and favouring ever more elaborate, explicit cost-effectiveness modelling of low risk easily quantifiable interventions while neglecting the more high risk “better approximately right than precisely wrong” kind of interventions.
I agree though that it’s hard to say whether this is better than funding say policy reform that would improve trade with emerging economies or biosecurity.
Yes, we should clearly aim to avoid precision bias. I don’t actually make donation decisions using comparisons of this kind—I just wanted to point out what I saw as a lack of clear “final benefit” description along the lines of “assuming a middling outcome, we’d expect to prevent roughly X tons of carbon/Y degrees of warning”.
But I wouldn’t be surprised if some figure like that was embedded in the report and I just couldn’t easily find it.
--
Also, it took me a while to find the section where the report explained potential reasons behind the (apparently) drastic undersupply of R&D funding: Here’s the explanation, which helped me get a better handle on why this cause has such high potential impact numbers behind it.
Have you spoken to Open Phil about this opportunity? Are you aware of any research they’ve done into R&D funding, or R&D policy grants they’ve made? It seems like this would fit under their “transformative basic science” or “global catastrophic risk” portfolios, and they’ve previously made at least one speculative grant with a small chance of sharply reducing emissions.
>>what I saw as a lack of clear “final benefit” description along the lines of “assuming a middling outcome, we’d expect to prevent”.
I think a thorough “final benefit” / “$ per ton of CO2 equivalent”/ “$ per degree of warming averted” calculation is not in principal outside of the realm of empirical investigation, but there are many difficulties here (e.g. the elasticity of clean energy demand, the comparative carbon intensities of other low carbon energy etc.). I might come back to that in case there is very strong demand for these numbers. But I also don’t think we need these calculations for the same reason that many high risks, high return grants lauded in the EA community do not need to include a “$ per life saved” calculation. I do have a bunch of what Bostrom calls crucial considerations in this report and I think EA research should head perhaps more in that direction.
But for what it’s worth we do mention the economic benefits of reducing global low carbon energy costs by several percentage points. They might be very large, because World Energy expenditure is in the trillions, [48],[49] and even a small reduction in cost by several percentage point might lead to large savings. Also there is a recent study which found that combining clean energy innovation with emission reduction policies reduces the costs of climate mitigation with a net present value of $3-6 trillion.[50]
Also, one economic model suggests that “if a carbon tax imposes a dollar of cost on the economy, induced innovation will end up reducing that cost to around 70 cents”.[73] Given that political acceptability is mainly a function of cost, making clean energy cheaper might make carbon taxes more likely. Just based only on this effect, it might make this a really good reason for donating to this, but again it’s hard to quantify the exact benefits.
>>Have you spoken to Open Phil about this opportunity?
I do not know OpenPhil’s official position on this, but there is a cell in “Open Philanthropy Project’s Public Priorities- Global Catastrophic Risks” spreadsheet which mentions that clean tech R&D might be a potential philanthropic opportunity. But the same spreadsheet also mentions says that Anthropogenic climate change (other than geoengineering) is not prioritized. I’ll definitely approach them though.
Just picking up on the importance, neglectedness, tractability table, Hauke, can I ask you to explain what you meant by those three terms (or, at least the last two) and how you see them as fitting together to give you an estimate of cost-effectiveness? I notice you did a fermi estimate too, so can you say what the relationship is between I, N, T and the fermi estimate? This isn’t a critical question—I’ve been thinking about cause prio a lot and I’ve realised it’s not clear to me how people use these concepts in their decision-making. Hence, if you could say a bit more that would helpful.
As suggestions:
is tractability: cost-effectiveness, resources requires to solve the problem, subjectively-perceived easiness, or something else?
Is neglectedness: resources going towards the problem? if so, how directly targeted at the problem did you have mind? Is it about counterfactual replacability? Something else?
Is the idea I, N, and T somehow give you an intuitive cost-effectiveness estimate and then you build the fermi estimate as an explicit follow up?
Sorry if this seems pedantic and I’m not engaging with the spirit of your post. The research looks very thorough and I’m glad you did it. As a non-expert on the subject matter I probably don’t have much of substance of add to that.
My understanding of these terms is roughly as follows:
Scale: general size of the problem. Determines the upper bound of what can be achieved. Determining the scale of a problem is quite arbitrary, because how do you draw the boundaries of ‘the problem’ and when is it completely solved?
Tractability: determines the average or global cost-effectiveness if you don’t know where you are on the curve (i.e. if you don’t know how much of the problem has been solved so far). Higher tractability means that the curve is steeper on average.
Neglectedness: determines the location on the curve and gets you the marginal or local cost-effectiveness. Because we expect the value curve to have diminishing returns, a good heuristic is ‘more neglected --> higher marginal value.’
I think where EA’s go repeatedly wrong with the application of the model is that tractability and neglectedness get confused: tractability should refer to solving the complete problem. If it refers to marginal tractability, then it double counts the neglectedness consideration. The report seems to do this:
Here, neglectedness is taken as a reason for tractability, while it should be a reason for marginal cost-effectiveness.
The SNT-model is also much more helpful for funding than for career choice, because neglectedness has linear implications for the value of extra funding, but more complex implications for an extra person doing work. Some skills are not very useful in the early stage of a cause area or problem, but become valuable only later. In general, I think personal fit is very important, and the SNT-model does not account for it.
I actually hope to write a longer post explaining all this in more detail, including some nice visual explanation I have of the SNT-model.
No sorry that’s incorrect. These are two separate points.
Clean energy R&D is neglected because only $22 billion globannually are invested—Norway could in theory triple this if they wanted to and it would have a very large effect on global emissions.
Carbon taxes are also neglected. But if Norway were to implement a carbon tax the effect on global emissions would be tiny.
Increasing public clean energy R&D does not necessarily require strong multilateralism or harmonized national policies. This makes it very tractable politically and uniquely positioned in the space of all climate policies as a decentralized approach.
Even if clean energy R&D spending would be relatively higher (say 100 billion), it might still be more tractable for a small country to increase it than to implementing carbon taxes.
Ah, I assumed the latter was a consequence of the former because they were in the same paragraph, my bad.
However, like Michael, I’m still a bit confused about the role neglectedness is playing in this analysis (and all other analyses). But don’t take that as criticism of your analysis. It often seems that neglectedness and tractability (and scale) are used as independent reasons to support a particular cause area or intervention, rather than that they are used as a coherent framework. It seems to me your argument would have been similarly strong if clean energy R&D was not neglected—if you could just show that additional spending would have big benefits.
I do not have a super strict definition of the ITN framework, but we are inspired by 80k’s ITN methodology. The arguments and findings from the ITN analysis, sometimes serve as inputs to the fermi estimate.
Tractability for instance we mention several times throughout the report:
“Public clean energy R&D is neglected: only $22 billion is spent per year globally. Many advanced economies such as the US could unilaterally increase this substantially i.e. even without international coordination—which makes this policy uniquely politically tractable. ”
“Increasing public clean energy R&D does not necessarily require strong multilateralism or harmonized national policies. This makes it very tractable politically and uniquely positioned in the space of all climate policies as a decentralized approach (see Figure 4).”
Or:
“Political tractability of carbon pricing approaches
Carbon pricing is becoming increasingly unpopular and politically difficult to implement.[173] One commentator writes that “the carbon tax’s fading appeal, even among groups that like it in principle, shows the difficulties of crafting a politically palatable solution to one of the world’s most urgent problems”.[174] It might be an even larger political challenge to increase the carbon tax to reflect the social cost of carbon (i.e. the true price of the externalities).[175] The political feasibility of a carbon tax is further decreased by the seemingly endless debates on how high it be should be (although it would make sense to set the carbon price to the marginal abatement cost, which is easier to estimate than the marginal social cost of carbon,[176] or use the lower bound of the social cost of carbon,[177] and/or simply err on the side of overestimating externalities, while reducing other non-Pigovian taxes).
On the positive side, carbon pricing might face less industry pushback and regulatory capture than many might assume: Major fossil fuel companies are advocating for carbon pricing.[178] This might be a case of ‘Bootleggers and Baptists,’[179] a phenomenon in which profit-driven corporations cause externalities (bootleggers) to align politically with socially motivated governments (baptists) trying to reduce externalities, as pushing for tighter regulation of their own industry (e.g. alcohol, carbon) gives them an advantage by making it harder for new competition to enter the market. On the other hand, the fossil fuel companies have invested over $1 billion on misleading climate-related branding and lobbying.[180]
In the appendix, we list two different ways of measuring national efforts to price carbon. The first is the country’s environmentally-related tax revenue as a percentage of GDP (e.g. gas taxes etc.). The second measure takes into account both carbon taxes and emission trading systems to calculate the effective carbon rate.”
“Cheaper clean energy technology might save the world a lot of money and might reduce both emissions and poverty. Many people also suggest that this would make a carbon tax more politically palatable.”
“Theoretically, a perfect global carbon pricing regime implemented early might have been the only policy needed to prevent climate change.[143] Leading economists agree that carbon taxes are a great policy intervention.[144] Increasingly, advanced economies do price or tax carbon emissions. A global carbon price would lead to lower emissions and incentivize the private market to build cleaner energy technology. Although there are proposals and increasing public support for a global carbon tax,[145] the biggest challenge still is that they do not seem politically palatable enough.[146] Some countries, such as Russia, derive a substantial part of their GDP from fossil fuels[147] and it might thus be in their interest not to adopt a carbon price.”
On neglectedness:
“Public clean energy R&D is neglected: only $22 billion is spent per year globally compared to $140 billion spent on clean energy deployment subsidies and trillions spent on energy.”
“But is public spending on clean energy R&D really neglected? Is it effective to spend more? We think so. Consider that, globally, only $22 billion in public funds are spent on clean energy R&D annually—this is only 0.02% of World GDP.[18] For comparison, world energy expenditure was 6% of the World’s GDP. This means we spend about 300 times as much on energy than on making energy better.
Why is there so little investment in clean energy innovation?
Generally, basic R&D is under-supplied at both the private and public level. There are several theoretical reasons for this:
On a global level, basic clean energy R&D is under-supplied by both governments and the private sector. Why? Because it suffers from the free-rider problem, as all basic R&D and public goods do. Countries and firms can just let others do the basic research and then reap the benefits because knowledge is hard to protect internationally. Private R&D cannot be protected perfectly because patents expire or industry know-how diffuses to other firms and not all rents from investments can be captured. This results in a socially suboptimal investment. In other words, additional public investment through basic R&D funding and subsidies increase social surplus, because private capital can only capture a fraction of the social surplus pie.
Generally, venture capital and the market neglect capital-intensive, high-risk, high-return, long time-horizon investments.
Clean energy R&D, in particular, is under-supplied because externalities of carbon are not priced adequately, leading to insufficient commercial applications for clean energy R&D.”
“First, generally, clean energy innovation is neglected by philanthropists. US philanthropists gave only $115,000 in grants to promote government clean energy R&D spending and only $20,000 to promote the role of government in fostering innovation annually on average from 2011-2015.[52] This suggests that there are likely still increasing returns to scale.”
“Climate change is relatively non-neglected
Climate change is a high-profile topic that many people work on. It is funded by both governments and big private foundations. Thus, even though clean energy innovation in particular has been relatively underfunded within the climate policy space, it is conceivable that in the future ITIF might receive grants for their clean energy innovation program from other funders, which lowers the counterfactual impact of donating to this project. In other words, comparatively, climate change is not very neglected. For instance, the risks and expected losses of pandemics are of a similar magnitude than those of climate change, yet the area is more neglected by other funders.[75]”
You might also be interested in the cell notes in this spreadsheet that give the very quick reason for all climate policies scores on the ITN framework.
Does that answer your question?