One of the most successful examples is the Home Energy Report—a simple letter that tells households how their electricity use compares to their neighbors. The effects are modest but remarkably consistent (around 1–2% reductions), and the intervention scaled widely across the United States. But there’s also been a long-standing puzzle: most of the impact appears to persist even years after the reports stop—something that doesn’t happen nearly as often in other domains like charitable giving, voting, or savings.

In this conversation, I’m joined by Alec Brandon (Johns Hopkins Carey Business School), co-author of “Do the Effects of Nudges Persist? Theory and Evidence from 38 Natural Field Experiments.” (Link) We discuss what explains this unusual persistence—and why the answer may have less to do with habit formation than with something more durable: technology adoption that “locks in” behavior.

Once you see the mechanism, it changes how you think about nudges—not just as a way to shift short-run actions, but as a tool for triggering longer-run changes in homes, policies, and institutions.

Enjoy the conversation and let me know if you which topics you would like to see covered!

Arvid

Introduction

Arvid Viaene: Because climate change is essentially an unpriced externality, the obvious solution is to put a price on it, either through a carbon tax or cap-and-trade. We’ve discussed those solutions already on multiple episodes. However, another complementary approach that has gotten a lot of attention in the past decade is changing behavior directly through nudges.

One example is sending a home energy report that tells people how their energy use compares with that of their neighbors. Research has shown that these types of reports can reduce average energy consumption by 1% to 2% consistently.

That is a great result, because it is generally very hard to change people’s electricity use. As a result, energy providers in the United States have widely adopted these reports, and policymakers have praised them heavily. The company that developed them was even acquired for more than $500 million.

While that is a great success story on the surface, there has also been a puzzle in the literature: the majority of the short-run effects persist even two years after the energy reports are discontinued. However, that result stands in contrast to other areas like charitable giving, financial savings, voter turnout, and so on, where those nudges do not persist.

So the paper we are going to discuss today figures out why nudges in energy conservation can be so successful in homes, and why they may be persistent in ways that differ from other contexts.

Once you get the idea—which is both simple and really cool—you may start to see opportunities to apply these insights to climate policy, other policy areas, and maybe even your personal life.

I’m happy to have Alec Brandon on. Alec is an author of the paper and an assistant professor at the Johns Hopkins Carey Business School. His research focuses on behavioral economics.

Using a variety of empirical methods, Alec has studied the long-term effectiveness of nudges in different areas, as well as the extent of racial profiling in policy. His research has been published in leading journals like Science and the Proceedings of the National Academy of Sciences.

Before joining Carey, Alec received his PhD in economics from the University of Chicago. Alec, welcome to the podcast.

Alec Brandon: Thank you.

Arvid Viaene: I’m excited to have you on. I also forgot to mention the title of your paper during the introduction, so let me do that now. The title is Do the Effects of Nudges Persist? Theory and Evidence from 38 Natural Field Experiments. What is your paper about, and what would you like people to take away from it?

Alec Brandon: Big picture, our paper is about trying to understand whether this really promising line of research on nudges can produce persistent, long-term effects. That matters in general, but it is especially important for something like climate change. If nudges do persist, the next question is why. And if we can answer that “why” question, then maybe we can replicate the success of persistent nudges and design them more effectively. That is probably the multi-sentence summary.

What the paper finds

Short-run nudges versus long-run effects

Arvid Viaene: I think that’s a really good summary of why this research matters. What did you find in the paper?

Alec Brandon: One of the things that motivated us was the mixed early evidence on whether nudges continued to change behavior after people stopped receiving them. Back in the earlier period—say around 2015—there was some evidence that nudge effects could persist for a couple of weeks or maybe a few months, but they tended to fade fairly quickly.

Arvid Viaene: What would be an example of that kind of nudge?

Alec Brandon: The examples that come to mind are nudges encouraging people to exercise more, turn out to vote, or give to charities.

In those settings, it did not really seem like nudges were transforming who people were.

But then there were a few papers on water conservation and energy conservation that found really striking persistence. Some water conservation studies found that a single letter led to savings that lasted for years.

There were also industry white papers and academic papers on the home energy reports we study, showing that 80% or 90% of the effect remained even after the reports were randomly discontinued.

That raised the question for us: why would nudges persist in one area but not in others?

The core idea: technology can lock in behavior

Alec Brandon: The simple idea we had was that maybe the reason nudges persist in energy and water conservation is that those are settings where people can adopt technology.

If someone tells you, “You’re using more energy or water than your neighbors,” you can respond by making a change to the home. That technology can then keep producing conservation even if behavior itself doesn’t continue changing.

Other behaviors are not really like that. Voting, charitable giving, and exercise do not have the same kind of built-in technological fix.

That observation is what set us down this path.

Arvid Viaene: Right. With voting, for example, you might get a nudge and then go vote. But at the next election, if you no longer get the nudge, you stop going.

Whereas with an energy report, the nudge might get you to install something more efficient, and then that change remains.

Alec Brandon: Yes, that is exactly the idea.

Why the authors were skeptical of habit formation

A different explanation from the standard story

Arvid Viaene: Did you already have that idea going in, or did it develop as you looked at the data?

Alec Brandon: We more or less had that idea going in.

At the same time that nudges were becoming popular, there was also a lot of work on habit formation using experiments, often with incentives. Researchers would incentivize a behavior, remove the incentive, and then see whether the behavior persisted.

There really was not much evidence of habit formation at the level needed to explain the persistence being found in energy and water conservation.

Some papers from around 2008 or 2009 might find that 5% or 10% of the effect persisted and call that habit formation. That may be enough to reject a null of no habit formation, but it is nowhere near large enough to explain the levels of persistence people were reporting for some nudges.

So we were skeptical of habit formation as the full explanation.

To be completely honest, the habit formation model began as a way to describe things like addiction to cigarettes or heroin. That story makes sense to me because there is a chemical component involved.

But with a brief incentive to exercise, save more money, or respond to a nudge, I don’t think that is really changing who people are. And nudges, by design, are supposed to be light-touch. They are not intended to transform identity.

So one building block of the project was skepticism about the usual mechanism people were pointing to.

The importance of households moving

Alec Brandon: A second building block came from the earlier Opower papers.

Arvid Viaene: Opower, by the way, is the company that sent out these energy reports.

Alec Brandon: Yes, thank you. Opower was the company that designed and developed the Home Energy Report.

In the earlier papers, the researchers mentioned that they had to drop homes when someone moved. They were doing that for econometric reasons—they wanted a balanced panel.

We don’t need to get too deep into that. But we noticed that the company could observe when someone moved, and we realized that feature could help separate the effect on the individual from the effect on the home itself.

How home energy reports work

The design of the intervention

Arvid Viaene: I think that gets to the core of your paper. Could you explain the setup of the energy report experiment?

Alec Brandon: Sure. Let me start with the report itself.

There were at least 100 of these home energy report experiments run between roughly 2008 and 2015, and they may still be running. The basic setup was that an energy provider partnered with Opower.

To demonstrate effectiveness, Opower would create a small control group—maybe 20% to 40% of homes—and then a treatment group that received these reports monthly or quarterly.

The letters told households how much energy they used, how much their neighbors used, and how much their most efficient neighbors used. They also included a simple evaluation of your performance.

If you used less than your efficient neighbors, you might get a smiley face. If you used more than your efficient neighbors but less than all neighbors, you got a neutral face. If you used more than all your neighbors, you got a frowny face.

Those letters were sent regularly. Opower also tested different frequencies, but the exact cadence did not seem to matter much.

Why movers reveal the mechanism

Alec Brandon: There was also another quirk: once the homeowner moved, the house was removed from the experiment and the letters stopped.

I do not think that was an intentional research feature. It was just common sense. The energy provider did not want the new resident receiving a rating based on someone else’s energy use.

That ended up being very useful for us. If the letters stop after the original resident moves, but Opower continues observing energy use in the home, then we can measure how much of the effect stays with the home itself.

That lets us separate the effect on the original person from the effect that persists because of something about the house.

Arvid Viaene: Because before that, the assumption was that people received the nudge and changed their own behavior in the home.

Alec Brandon: Exactly.

The main result - More than half of the effect stays with the home

Alec Brandon: The effect of getting the home energy report on the household is about 1% to 2%. In our sample, it was 2.1%.

Then, once the initial resident moves, the report still has an effect of about 1.1% on the home. So a little more than 50% of the original effect remains after the original resident is gone.

Arvid Viaene: And that is the technology story.

Alec Brandon: Yes. We attribute that remaining effect to technology adoption.

The rest we attribute to habit formation, or at least to some role for habits.

Renters versus homeowners - Why the distinction matters

Arvid Viaene: One of the most interesting parts of your paper is the difference between renters and homeowners.

In general, you find that about half of the total effect is habit and half is technology. But the renter-owner comparison is especially interesting.

Alec Brandon: That analysis started partly as a way to convince referees that what we were doing made sense, but it turned into an interesting result in its own right.

Earlier papers on the Home Energy Report found that whether someone rented or owned their home did not affect whether the report produced energy savings.

That is interesting because, especially in the United States, there is not much of a culture of renters adopting energy-efficient technology.

Part of that is contractual. If you rent, you usually are not allowed to make major changes to the property.

But it is also financial. Why would you invest in energy-efficient technology if you are not going to live there long enough to recoup the benefit?

Renters mostly change habits, not technology

Alec Brandon: What we find is that renters respond similarly to homeowners while they are in the home. But once the renter moves out and a new renter moves in, none of the effect remains.

That suggests renters are changing something significant while they live there, but that change leaves with them. So in that group, the persistence seems to come from habits, not technology.

If someone believes in habit formation, this is a result they can really point to.

Arvid Viaene: That makes sense. Renters mostly have one way to reduce energy use: they change their behavior.

They turn off lights more consistently, adjust how they use appliances, and do all the small daily things that reduce electricity use. In that sense, their changes are cost-free.

When they leave, they take those habits with them.

Alec Brandon: Yes, though I would add that in an accounting sense they are cost-free. There may still be psychic costs or effort costs to adopting those habits.

I am not an expert on that specific question, but I agree with the general point. In terms of standard measurable outcomes, habits are appealing because you are getting something without a direct capital expenditure.

The hidden cost of persistent nudges - Technology adoption changes the cost-benefit calculation

Arvid Viaene: One of the important points in your paper is that when homeowners respond by adopting technology, that is not cost-free. It may have been overlooked in earlier cost-effectiveness discussions.

Alec Brandon: Yes, that is one of the main implications we try to emphasize.

A lot of people want to evaluate whether interventions work, whether in government or in the private sector. I think that kind of evaluation is extremely important.

But it is tricky, because the outcomes you observe may not capture everything people are doing in response to the intervention.

In our setting, if homeowners are adopting energy-saving technologies because of the reports, then those expenditures should be counted when you compare the benefits of the program to its costs.

We did not have direct information on exactly what technologies people were adopting, so we used back-of-the-envelope estimates from the literature on the cost per kilowatt-hour saved through technology adoption.

We chose a lower bound and an upper bound.

The exact estimate of net benefits depends on those assumptions. But the broader conclusion does not: the program still has positive net benefits either way.

Arvid Viaene: So it remains net beneficial, but the total benefits are meaningfully smaller once you account for those costs.

Alec Brandon: Yes. It takes a chunk out of the benefits.

That is basically just accounting, and accounting points are nice because you can be fairly confident you are right.

Why earlier papers missed the technology channel

Rebate data was too narrow

Arvid Viaene: Earlier papers, such as Allcott and Rogers and another by Ferraro and coauthors, looked at technology and seemed to rule it out. Why are you more confident their conclusion was incomplete?

Alec Brandon: Those papers were broadly contemporaneous, and they looked at related interventions.

The Allcott and Rogers paper, on energy conservation, used data from utility rebate programs. The idea was to see whether people who got the Home Energy Report were more likely to participate in rebates for energy-efficient purchases.

They found basically no difference between treatment and control. Their back-of-the-envelope conclusion was that maybe only 1% of the report’s effect came through that rebate channel.

The water conservation paper used an early version of a movers design and found that no effect remained in the home.

I suspect that in both cases, these analyses were somewhat speculative and placed toward the end of the paper.

In the case of the rebate analysis, I think the issue is that many of the relevant technology changes are too small or too inconvenient to show up in rebate data.

If someone installs efficient light bulbs or adds a door sweep, there may technically be a rebate. But are people really going to file the paperwork for that? Probably not. Those programs are notoriously undersubscribed.

So unless the Home Energy Report was causing large, contractor-driven renovations, rebate participation was probably the wrong thing to measure.

Observing the home directly is different

Arvid Viaene: Right, and your design is different because you do not need to infer behavior from rebate participation. You keep observing the home after people move out.

Alec Brandon: Exactly. It is always nice to have data that directly tells you what people are doing, but we basically accepted that this might be impossible in this setting.

The kinds of changes people make may simply be too small to observe directly.

That is actually a broader challenge with nudges. Nudges usually have small effects, but they are cheap enough to implement at large scale, which makes it possible to detect those effects.

The flip side is that small effects are hard to unpack mechanistically. It is hard to run surveys with high response rates when you are just sending letters. It is hard to get the “smoking gun” evidence people would ideally like.

So our approach is to infer the mechanism from what remains in the home. That is a strength, but also a limitation.

Arvid Viaene: Right. You cannot identify exactly which technology people installed. You can only see that something about the home changed.

Alec Brandon: Exactly.

What this means for climate policy

Nudges work better when paired with something durable

Arvid Viaene: One thing I really like about the paper is that it changes how you think about nudges.

Instead of only asking whether a nudge changes behavior in the short run, you ask whether it can trigger a technological or institutional change that keeps affecting behavior over time.

For example, with voting, maybe the nudge could get someone to install an app or sign up for a system that keeps nudging them. In climate policy, maybe the key is to get people to adopt something that keeps the effect going.

Alec Brandon: I think that gets to the most important implication of the paper.

Nudging for the sake of nudging is still worthwhile. It helps us learn what works, and the things that work can sometimes be scaled.

But I think it also makes sense to ask what the underlying response actually is. What do you expect people to do in response to your nudge? And are the conditions there for that response to stick?

In energy, that is straightforward. If there is a low-cost technology you want people to adopt, then a nudge that grabs attention and gets people to consider action can complement that technology nicely.

So instead of taking a purely reduced-form approach—“I do not care how people respond, I only know the experiment works”—our paper is pushing people to think more concretely.

What technologies would be useful if people adopted them today? Can you design a nudge that gets attention and leads to adoption?

Or, alternatively, can you pair a nudge that works in the short term with something that makes long-term persistence more likely?

Pair nudges with defaults or new incentives

Alec Brandon: For example, maybe a voting nudge could have stronger long-term effects if it also included a form that helps people sign up for mail-in voting. That would reduce the cost of repeating the behavior in the future.

Or in energy, maybe the nudge could encourage enrollment in critical peak pricing, which changes the incentives people face over time.

That is still a conjecture, but that is where we hope people take the paper: thinking more clearly about what exactly is going to produce the long-run effect.

Arvid Viaene: Yes, being more rigorous about what is actually changing.

I also like your point that behavioral economics is very good at grabbing attention. The smiley-face report gets people to notice something. Then you can use that moment to connect them to a pricing program, a technology, or a more durable change.

Alec Brandon: Exactly.

Behavioral economics offers a very useful toolkit for getting people’s attention. The field has a more uneven track record when it comes to very long-run effects.

So one promising direction is to combine those tools with more traditional economics—changing incentives, reducing friction, encouraging technology adoption.

That could let you get the best of both worlds: the immediate change in behavior and the more durable effects that come from structural changes.

Examples beyond the paper - Heat pumps, solar panels, and framing

Arvid Viaene: I think that is especially relevant for climate and energy policy.

Take heat pumps in Europe. Energy prices are high, and for many homes heat pumps can be a very good option. But a lot of people are not aware of what they are or how they work.

Behavioral economics seems useful here because it can grab attention and help people recognize that something could genuinely benefit them.

Another example is a paper by Verboven and De Groote on solar panel adoption in Belgium. Unlike in the United States, Belgium had a very complicated subsidy system.

It was not something simple like “you buy this and get 50% back.” Instead, you bought something for €10,000 and got the rebate gradually through electricity credits over many years. People just did not realize how favorable the deal was.

That seems like a case where behavioral tools could help people understand how valuable the policy actually is.

Alec Brandon: I agree.

One way to put that is that prices are always framed in some way. There is no such thing as a frame-free price.

Behavioral economics gives us tools to think about which frames are better and which are worse.

What you are describing in Belgium sounds like a case where the policy may have been framed in a way that made it much harder for people to understand how attractive it actually was.

Additional result from the paper - Homes with electric heating show more persistence

Arvid Viaene: Is there anything else from the paper that we have not covered and that you would like to add?

Alec Brandon: The only other thing I would emphasize is a result that is sort of a counterpart to the renter finding.

We also had a similarly sized sample of homes that used electric heating rather than natural gas. Since our outcome is electricity use, those homes had more scope to generate savings through technology adoption.

And that is exactly what we see. In those homes, around 60% to 65% of the initial effect persists, compared with about 50% on average and zero for renters.

So the story I tell myself is that people may prioritize technology adoption because it is the easiest way to get a better report card from the utility.

But if that option is not available, and you keep sending the letters long enough, maybe people do adopt habits instead.

That is a conjecture, but I think it is a useful way to connect the different results.

Related research on energy technology

Smart thermostats may not save energy

Arvid Viaene: Are you doing any further research in the energy nudges space?

Alec Brandon: Not at the moment. But I am finishing another paper that your listeners might find interesting.

It is a more conventional technology-evaluation paper in which smart thermostats were randomized.

In the United States, there is a lot of subsidy money available for people who replace their thermostat with a smart thermostat. These thermostats connect to the internet and can be controlled from your phone.

We studied a field experiment in California where people were recruited and, if randomized into treatment, got a smart thermostat installed for free.

And we do not find any energy savings from the people who received the smart thermostat compared with those who did not.

So I am not claiming that technology is always the answer. Smart thermostats do not seem to deliver the kind of energy savings that households in the home energy report study were apparently finding through other changes.

Arvid Viaene: That also shows the kind of critical mindset you need as a researcher.

Even if you are interested in technology as a mechanism, you still need to test whether a specific technology actually works.

So if anyone listening works at an energy provider, has a promising intervention, and wants to run a serious field experiment, Alec is clearly someone worth contacting.

Alec Brandon: Yes, feel free to email me.

Arvid Viaene: Alec, thank you so much for taking the time.

Alec Brandon: My pleasure.

Introduction: Welcome back to Part 2 of my conversation with Richard Tol.

In the first part, we focused on the structure of the FUND model: what integrated assessment models are trying to do, why adaptation matters, and why climate damages depend not only on warming itself, but also on development, institutions, public goods, and technological change.

In this episode, we move from model structure to model use. We talk about the social cost of carbon, how the Obama-era EPA worked with models like FUND, DICE, and PAGE, and why Richard argues that the hard part is often not running a model, but understanding it well enough to use it responsibly.

That matters because once a model enters policy, its output is no longer just an academic result. It can shape regulatory analysis, legal reasoning, and the way governments justify action. And at that point, disagreements about models are no longer purely technical. They become disagreements about assumptions, uncertainty, judgement, and politics.

So this second part is about what happens when integrated assessment models leave the seminar room and enter the policy process. We discuss the social cost of carbon, why single headline numbers can be both useful and misleading, why misunderstood models can be dangerous, and what the debate around IAMs reveals about the uneasy boundary between economics and climate politics.

And if you have not yet listened to Part 1, I’d recommend starting there, because that episode unpacks the logic of FUND itself — and that gives the policy debate in this episode much more context.

If Part 1 was about how the machinery works, Part 2 is about what happens when that machinery is actually used.

Arvid Viaene: When I started the introduction, I mentioned how under the Obama administration they used three models—DICE, PAGE, and FUND—to estimate the social cost of carbon. Those were, as I understand it, independently developed, so in that sense you get equal weighting. How did you view that process by the EPA or the Obama administration’s interagency working group? Because to me, from a distance, it always seemed like a good way to do it. You said there shouldn’t be a single estimate, but as a policymaker you do ultimately need one number to put on a carbon tax.

Richard Tol: Yes, absolutely. It is right and proper that the EPA does the filtering process and then comes out with a single number. That is not my job. It would be entirely wrong for me as a professor to narrow the range to a single number. That is the job of policy advisers, not policy analysts.

The experience with the EPA was very interesting, and I was not involved in the decision-making at all. What the EPA did was spend two years understanding these three integrated assessment models and running them. That tells you something about what the EPA was like then.

Arvid Viaene: Yeah—they took two years to understand them.

Richard Tol: And it took two years not to learn how to run the model, because that certainly doesn’t take two years. Depending on the version, it’s often just a single command.

What they spent those two years on was having a team of analysts fully understand the model—every parameter—and understand it so well that they could explain it to their political bosses. That was very enriching, because the EPA hires PhDs from top programs. Working with people who are really clever and who devote a lot of time to understanding your work is a great experience.

After that, they understood the models so well that some of them were actually contributing to the literature on the social cost of carbon and climate economics more generally.

Then they took it through the political process, and I had no influence over that. They were not interested in my opinions on that at all. One of the debates we had—which later came back to bite them—was whether the social cost of carbon for the United States should reflect only impacts falling on the United States, since that is under U.S. jurisdiction, or whether it should also include impacts caused outside the United States.

We had long debates about that. In the end, it was the politicians and the lawyers who decided, and they never presented a U.S.-only social cost of carbon. And of course, that was the first thing Trump changed.

Arvid Viaene: Yeah, exactly. I actually did a solo episode on that. One of the few tweaks Trump made was to look only at U.S. estimates and change the discount rate, which drastically lowered the figure.

Richard Tol: Mm-hmm. Yes, absolutely.

How models are misunderstood

Arvid Viaene: Let me quote something from your website because I think it’s really interesting. On the FUND model website, you write: It is the developer’s firm belief that most researchers should be locked away in an ivory tower. Models are often quite useless in inexperienced hands, and sometimes misleading. No one is smart enough to master in a short period what took someone else years to develop. Not understood models are irrelevant, half-understood models treacherous, and misunderstood models dangerous.

In that sense, it sounds like EPA took a good course by spending two years understanding the models. But that made me wonder: what do you think are the most misunderstood aspects of the FUND model, and how have you seen that translate into misuse?

Richard Tol: That quote does not refer to the EPA. Absolutely not. That was a very enriching experience. The quote reflects, first, my general understanding of my fellow academics.

There are two things I want to say about this. One is the Edmunds strategy.

Arvid Viaene: The what? The Edmunds—

The “Edmunds strategy” and unrealistic premises

Richard Tol: The Edmunds strategy. Edmonds is a prominent figure in integrated assessment modeling and has advised on environmental and energy policy for 40 years or more.

One thing Edmonds used to do when presenting results from his models was say things like: “Yes, we can meet this target if we scale up nuclear by so-and-so much”—for example, if you build 400 nuclear power plants in the next 20 years.

There were always two reactions in the room when he said that. The people who understood nuclear power would fall over laughing, because the idea of building 400 nuclear plants in 20 years, when we had only built about 200 over the previous 40 years, was obviously unrealistic.

So Edmonds gave the technically correct advice: if we could expand nuclear really fast, we could make a serious dent in CO2 emissions. But half the room understood that the premise was absurd. The other half heard only, “We can do this,” and walked away with the wrong impression—that these very stringent emissions targets were economically and technically feasible.

That is what I mean when I say that if you do not understand the model, you can walk away with the wrong conclusion. Some people use that as a strategy.

A case study in misuse and version control

The other episode that remark refers to is Ackerman, who took our model, changed it, found ridiculous results, and then blamed us. In particular, Ackerman claimed that in the model we divided by zero, which is not something you should do—and if you try to do that in numerical code, it generally does not work.

Arvid Viaene: Okay, yeah.

Richard Tol: Ackerman was particularly dishonest because we explained to him many times that we did not divide by zero, and that there was no reason to think we did. We had all sorts of checks in the model before the final result emerged, so even if we had tried to divide by zero, or divide by something close to zero, we would have caught it. But he published the claim anyway.

Arvid Viaene: So after you told him this wasn’t something your model did, and that there were many checks before it got there—this was over multiple conversations—

Richard Tol: Yes.

Arvid Viaene: He still published results saying that is what you did?

Richard Tol: Yes. Which of course served a political agenda in his case, namely attacking one of the three assessment models used for cost-benefit analysis at the time.

We learned lessons from that. One of them was to put the code online—not just on a website, but now on GitHub with version control and everything. So now you can’t just take our model, change it, and then claim we made a mistake. We can show that you made the mistake, which we couldn’t do back then because we had no version control.

It was not a pleasant experience, as you can imagine, because Ackerman was reasonably prominent in certain circles. A lot of people believed him, and a lot of people wanted to believe him. But it was just nonsense.

Arvid Viaene: Yeah, okay. I think that helps frame that quote.

Criticism of IAMs and debates around damage functions

Nordhaus, politics, and historical context

Arvid Viaene: Another quote of yours I wanted to get to is about how climate estimates are never politically neutral: for some they are too low, and for others too high. You write that an integrated assessment model like FUND is used to advise policymakers about proper and not-so-proper strategies, but it always reflects the developer’s worldview and is therefore regularly contrary to political rhetoric and occasionally politically incorrect.

That struck me because I once saw an economist on several podcasts saying Bill Nordhaus is “climate’s worst enemy” because the damages in DICE weren’t large enough. I wondered whether, as one of the authors of a leading integrated assessment model, you’ve seen that same tension.

Richard Tol: The guy you’re talking about is Steve Keen, right?

Going back to Nordhaus: Nordhaus worked in the Carter-era White House, and he was one of the architects of the early investments in renewables. Carter had that famous stunt of putting solar panels on the White House. That was a bit ridiculous because they were very expensive and did not generate much electricity, but another thing Carter did was start the research program into renewables that is now paying off big time. Had that not been started in the 1970s, we would not be where we are now.

Nordhaus was one of the architects of that. Throughout his career, he has always advocated for climate policy, and usually for more stringent climate policy than U.S. politicians wanted, including under Clinton-Gore. Nordhaus was far greener than Clinton and Gore when they were actually in office.

He also, with his brother, helped design the sulfur emissions trading scheme, which became the blueprint for emissions trading for carbon dioxide and other greenhouse gases in Europe. He also helped persuade President George H. W. Bush to sign the United Nations Framework Convention on Climate Change. During the Rio negotiations, the DICE model was running in the background to see whether the U.S. could afford to sign on.

Without that reassurance from one of the most prominent macroeconomists in the United States, I doubt Bush would have signed the UNFCCC.

So the idea that Nordhaus is the enemy of climate policy is historical revisionism on an epic scale. It’s just people who do not understand how things really worked, or what he actually did.

A lot of that fire has been directed at Nordhaus, but he’s handled it cleverly by not engaging. He writes papers; he very rarely writes op-eds or gives interviews, and he definitely doesn’t do social media.

Now, I do those things, as you know, and that’s one reason I’m here. So I draw a lot of fire as well, mostly from Greens who think I’m the devil. But I have advocated for a carbon tax since the beginning of my career—except in Europe, where I’ve said the price of CO2 permits is roughly correct. In most of the rest of the world, I’ve said for the last 35 years that the price is too low.

As you noted earlier, I helped formulate climate policy under Obama and Biden, and indirectly even under Trump, because Trump wanted to set the social cost of carbon to zero. But the courts stepped in and said the estimates were sufficiently robust that you could not set it to zero.

That robustness was not just my work—it was Nordhaus and Chris Hope as well. Apparently our work was strong enough to withstand the legal challenge.

I also helped formulate the carbon tax in Ireland and the landfill tax in the UK. So the idea that I am against climate policy, or that I have hindered it, is just wrong. People just don’t know the facts.

At the same time, people who think climate change is a hoax—or invented by the Chinese or Russians or whatever—don’t like me either, because I think climate change is real, caused by humans, and a problem that should be solved.

Arvid Viaene: Thanks for that.

I also wanted to add something from one of your Substack posts, “Economic Impact of Climate Change.” You write that many people express skepticism about the economic impact functions used in integrated assessment models for cost-benefit analysis, especially the modest impacts at very high warming. But you call this a red herring, because the damages are already large enough to justify keeping warming well below 3 degrees Celsius. The assumptions about what happens at 4 degrees may be spectacularly wrong, but they do not influence the model results.

I think that’s important because sometimes people say the damages aren’t big enough, but as you say, the assumed damages are already sufficient to justify climate policy.

Why extreme-warming damages may not drive model optima

Richard Tol: Let’s get a bit technical. What matters in an optimizing model like DICE is the value function, not the utility function. What matters is what happens in the optimal scenario.

In the DICE model, temperatures rarely get above about 3.5 degrees, and it’s a model without uncertainty. So really it is irrelevant what happens above 4 degrees. You can make the impact function extra steep after 4 degrees—you can multiply everything by 10 or 100—and it won’t affect the result because the model never goes there.

What I suspect is that people who are not mathematically trained look at the equations and parameterizations and focus on the objective function instead of the value function. They just get it wrong. For people without a PhD in economics, I understand the confusion. They look at the functions and think: this can’t be right.

The problem is that there is actually very little literature on the impacts of climate change at 4 degrees or 8 degrees of warming. Most studies focus on 2 or 3 degrees, maybe 4 at most. So those are your calibration points. Beyond that, you are extrapolating.

We know very little about those worlds. But fortunately, what we find is that even with these assumptions, we recommend a carbon tax that ensures we don’t go to those places about which we know so little. That is a good thing. I don’t know what a 4-degree world would look like. It seems very scary.

Cost-benefit analysis vs. European climate targets

Why EU climate policy favored cap-and-trade

Arvid Viaene: Yeah, I think so too.

I also wanted to ask about cost-benefit analysis and EU climate policy. I should say I’ve really enjoyed your writing. I didn’t know you before except through the FUND model, but I’ve been reading your papers and blog posts, and I really appreciate the style.

One of your posts is on the role of cost-benefit analysis. And I want to get to EU climate policy because there it’s mostly quantity targeting—net zero, cap-and-trade, fixed emissions quantities. I’m very U.S.-trained by Michael Greenstone, so I’ve always thought in terms of the social cost of carbon and cost-benefit analysis.

You wrote: Cost-benefit analysis has been used to propose a target for greenhouse gas emissions reduction. This inevitably starts a brawl because cost-benefit analysis forces you to make explicit all assumptions and value judgments that imply said target. There are other, less abrasive ways to set targets, but those can be reverse-engineered to reveal the implicit assumptions that make them optimal in the sense of cost-benefit analysis. I think it is better to be upfront about your assumptions and values. Cost-benefit analysis is a good way to get published in an economics journal. It is less suitable for climate policy advice.

I agree that it’s better to be upfront about assumptions and values. But I wanted to hear more about why cost-benefit analysis is good for economics, but less suitable for climate policy advice.

Richard Tol: If you want to be an academic, you should be honest. If you want to be a politician, you should not. That’s just not how you build coalitions. There is an inevitable conflict between the two.

The reason the EU went for cap-and-trade rather than a carbon tax is not that they did not want a carbon tax, or that the Commission’s policy analysts did not understand the differences. In fact, they were trained at places like Harvard and MIT and knew very well from Marty Weitzman’s work that a carbon tax is theoretically superior to cap-and-trade.

The reason they chose cap-and-trade was political. It had to do with the prospect of tax harmonization in the EU. The British and the Irish basically said there would be no European tax, so the next-best alternative was cap-and-trade.

Once you choose cap-and-trade, you immediately get into the question of what the target should be. Environmentalists also like the idea of capping the maximum amount of pollution. So it was much more political than analytical or economic.

In principle, it is not a terrible policy. You can quibble with things, but the alternatives would have been worse.

The targets politicians have set in Europe are very stringent, but again, this is politics. The political strategy is to promise to do a lot long after you have left office while doing relatively little while in office. That has essentially been the strategy of European politicians. That is why we have targets for 2050. That is still four or five elections away. It’s not really mytarget.

What we now see happening in Europe is that politicians are beginning to backtrack—not on 2050, which is still far away, but on current climate policy. People are starting to realize that this is expensive, and perhaps the short-run targets should be relaxed, even if the long-run ones remain.

Arvid Viaene: Yeah, okay. Thanks.

Richard Tol: And this goes back to cost-benefit analysis: it’s not free. You need to take both costs and benefits into account.

Has the social cost of carbon been “discredited” in the EU?

Arvid Viaene: Exactly. I once read in a policy book on EU climate policy that the social cost of carbon had been discredited in political circles. I never quite understood what they meant. Have you heard that idea—that the social cost of carbon has been discredited at the EU level?

Richard Tol: Well, they never liked it because it wasn’t high enough to justify the targets. The EU is obliged to do cost-benefit analysis for any major policy initiative, including climate policy. But if you look at the analyses published by the European Commission, they are never really proper cost-benefit analyses.

They are always distorted because they know they cannot justify the long-term targets with a textbook cost-benefit analysis. The author of the first climate cost-benefit analysis by the European Commission is actually an old friend of mine, and he told me: “Yes, I’m doing it wrong. That’s what the political masters told me to do.” And it has been like that ever since.

Arvid Viaene: Got it. Okay. Thanks, because that had always been a little confusing to me. Coming from the U.S., where one president comes in and changes the number dramatically, cap-and-trade seems more stable in the short run.

I’ve already enjoyed this conversation a lot and learned a lot. Is there anything we haven’t touched on that you would like to add?

Richard Tol: No, I think we have covered most of what you intended to cover.

Arvid Viaene: Yeah, I think so too.

Current research: Transfers, population, and welfare assumptions

Arvid Viaene: I think the only thing we haven’t really covered is the frontier—what you’re working on now. You’re clearly still writing a lot of papers, and it sounds like the meta-analysis is taking a lot of your time.

Richard Tol: There are two things I’m working on at the moment. One, going back to Schelling—I’m a big fan of Schelling—is trying to quantify the income transfers implied by climate change.

We have a paper doing that at the national level, and it turns out to be a bit different from what people think. A lot of people think the income transfer implied by climate change is from rich to poor—that the rich emit, and the poor suffer. That is actually not true, because the emissions intensity of middle-income countries is higher than that of rich countries.

So rich people, relative to their income, do not emit that much, and they are also not very vulnerable to climate change. As a result, the transfer is actually more from the poor to the middle-income than from the poor to the rich.

Arvid Viaene: Oh, I see.

Richard Tol: That paper is basically done. We are doing the same for income classes and for ethnicities, and the ethnicities work is something I’m particularly excited about.

The other thing I’m working on is endogenizing population growth in these models, and especially working through the welfare implications. The standard assumption in most of applied economics is that social welfare is proportional to the number of people times average utility. That’s sort of the Benthamite view of ethics.

In the climate change case, that can lead to very peculiar results. If climate change slows economic growth—and there is good reason to believe it does—and if slower economic growth slows the demographic transition, then climate change implies that more babies will be born in the future.

In a Benthamite model, that is actually a good thing, because Bentham says the more the merrier. If you just plug those assumptions in, then you should actually subsidize CO2 emissions because that means more babies.

If you then add in the mortality effects of climate change, that completely reverses the result and you get something like the Bressler result, where the social cost of carbon should be multiplied by 10 or 100.

But if you recalibrate the model, switch to a less Benthamite and more Millian welfare function, or introduce ideas like a life worth living in a Blackorby-type approach to social welfare, then that result disappears as well.

So this will probably be an intellectually interesting paper, but numerically it is disappointing. At the end of the day, all these effects cancel out and I’m back to something like the Nordhaus result.

I have four or five moving parts in the paper that are all interesting, and after calibrating everything, it all cancels out. That probably rules out publication in Nature or Science, because they want dramatic results. But it may be more interesting for an economics journal.

Those are the things I’m currently working on in the climate space.

Arvid Viaene: Cool, awesome. Thank you so much for taking the time. I really enjoyed this. One of my goals was to understand more about the FUND model—its history, insights, and design choices—and I definitely got that. I also hope this helps other economists understand the history and the reasoning behind the model.

I feel that hearing the researcher talk about the history and implications brings the model to life much more than simply reading an academic paper.

Richard Tol: Well, absolutely. We can say things here that we could never write in a paper, right?

Arvid Viaene: Exactly. So thank you so much. I think this will definitely help with that.

Arvid Viaene: Hi, and welcome to another episode. Climate change is the mother of all externalities. It is larger, more complex, and more uncertain than any other environmental problem. Those are the words my guest wrote in 2009. As an economist, the natural question is: what are the damages of those externalities?

What do those damages consist of? How large are they? And what are the uncertainties? My guest today, Richard Tol, has been one of the leading scholars trying to answer those questions, in particular through the use of an integrated assessment model called the FUND model. FUND stands for the Climate Framework for Uncertainty, Negotiation, and Distribution.

This type of model takes estimates of climate change and economic outcomes and turns them into estimates of economic damages. We’ll talk much more about that later. But first, I want to provide some context on the importance of the FUND model. When I was doing my PhD in economics from 2012 to 2018, there were three leading integrated assessment models, as I saw it.

One was Bill Nordhaus’s model, for which he later received the Nobel Prize in Economics. Another was developed by researchers at the University of Cambridge. And the third was the FUND model by Richard Tol. These three models were used by the Obama administration to arrive at a number for the social cost of carbon, the guiding figure for cost-benefit calculations in the United States related to climate change.

So these models have greatly shaped U.S. environmental policy.

Let me also give you some of Richard’s bio, which is very impressive. Richard is a professor in the Department of Economics at the University of Sussex and professor of the Economics of Climate Change at the Institute for Environmental Studies and the Department of Spatial Economics at Vrije Universiteit Amsterdam.

He is a member of the Academia Europaea and a fellow of the Royal Economic Society. Richard received an MSc in Econometrics in 1992 and a PhD in Economics in 1997 from Vrije Universiteit Amsterdam. To give you an idea of his impact, he has over 300 journal publications with more than 100 co-authors.

He is ranked among the top 100 most-cited economists in the world, as well as the top 100 most-cited climate scientists. He has published two books, three edited volumes, and many smaller publications. He specializes in the economics of energy, environment, and climate, and is also interested in tourism and scientometrics. So, Richard, welcome to the podcast.

Richard Tol: Thanks for having me.

What is an integrated assessment model?

Arvid Viaene: When I started this podcast, a conversation with you about FUND was actually on my wish list, so I’m very excited to have you on. But not all of my listeners may be aware of what integrated assessment models are. Could you give us a sense of what they are and what they are used for?

Richard Tol: Integrated assessment model consists of three words, right? The last one is model, which is essentially a mathematical or computational representation of how we think the world works.

The word assessment refers to the fact that these models are meant to advise policy. They’re not designed to further our understanding of reality; they’re designed to improve policy.

And the word integrated, the first word in integrated assessment model, means that the model is constructed to respect the boundaries of the problem, rather than the boundaries of academic disciplines. So in the case of climate change, you would have demographic components, economic components, engineering components, a carbon cycle—that is, how CO2 moves through the atmosphere and other carbon sinks like the ocean and the terrestrial biosphere.

You would have a climate model, and you would have impact models that are partly economic but also partly related to human health. So you span all the disciplines necessary to understand the climate problem.

The start of FUND - From econometrics to climate negotiations and cost-benefit analysis

Arvid Viaene: Awesome. Thank you. I’m wondering what got you started on these types of models. What made you decide to pursue them?

Richard Tol: I don’t think it was my decision at all. Just after I graduated, I was looking for things to do, and I found this job at the Institute for Environmental Studies. I’m still affiliated with them.

Even though my original training was in econometrics and statistics, they put me on this project. It was much more about cost-benefit analysis and a lot of game theory about how to set up international negotiations around climate change.

This was not my first choice, and in the beginning I didn’t really like it. But after a while you get used to what you’re doing, you get better at it, and it becomes more interesting as you understand more of it. So it was not by design; it was an accident. As John Lennon says, life is what happens to you while you’re busy making other plans.

Arvid Viaene: Yeah. And was it then part of your PhD, that they put you on this project?

Richard Tol: This eventually turned out to be my PhD as well. I started in 1992, actually, on this project, constructing this integrated assessment model, and that became a major part of my PhD.

Building a multi-regional model in the early 1990s

Arvid Viaene: Yeah, because at the time, I think Bill Nordhaus published his first paper in 1992, or maybe earlier, on the DICE model. How did you go about constructing the FUND model? To me it seems like such a huge exercise. There are so many components that just getting started seems daunting.

Richard Tol: It’s been a long time, right? Nordhaus’s work was known at the time. Actually, what we planned to do was build a multi-regional version of DICE. At the time, we didn’t know about Zili Yang and the RICE model. That was already fairly advanced, but we weren’t aware of it.

We were aware of the work of Carlo Carraro and Scott Barrett. Their work was circulating as working papers at the time. So essentially the plan was to build a multi-regional version of DICE and deviate from Barrett and Carraro by allowing heterogeneity across regions. At that time, they assumed every country was the same, which is a peculiar assumption that I still don’t understand how game theorists worked with.

So that was the starting point and the aim. How do you start building a model? You start by understanding what needs to go into it. We had a good bit of guidance from Nordhaus: what the components were and what they might look like. Not just Nordhaus—the CETA model by Peck and Teisberg was actually slightly earlier.

We had access to those as well. And then you just start building. The main challenge was regionalizing the model and regionalizing the impacts of climate change. Some of Nordhaus’s work was only available in draft at that stage, but it was still a big help.

Arvid Viaene: Right. I think one of the big differences at the time versus DICE was that you started creating these 16 regions, whereas DICE had—

Richard Tol: Nine. Sixteen came later, yes.

Arvid Viaene: Okay—whereas DICE was just one model for the world. So once you got into that, were there other parts of FUND that started to differentiate it from the other models?

How FUND differs from DICE and PAGE - Sector-by-sector impacts and adaptation dynamics

Richard Tol: One thing FUND has always done differently from all other integrated assessment models used for cost-benefit analysis—apart from the GIVE model by RFF—is that we have separate impacts for different sectors. In that sense, we are similar to GIVE.

I never quite understood why all sectors should move in tandem, or why they should all have a quadratic functional form. Conceptually, and more importantly, because different sectors develop differently depending on how the economy grows, you naturally create dynamics in your impacts.

That’s something a structure like PAGE or DICE completely lacks. If you look at the equations in DICE, the impacts of climate change are a function of climate—really a function of temperature. Then they are just scaled up and down with the size of the economy. But things like the provision of public goods or the structure of the population simply aren’t there.

We know those things are important because adaptation is terribly important for the impacts of climate change, and a good part of adaptation has to do with the provision of public goods. Nordhaus essentially assumes that the provision of public goods is constant across space and time, which is a very peculiar assumption.

Similarly, if you look at health impacts, things like malaria particularly affect children between zero and six months old, while heat stress particularly affects the elderly. Assuming that the structure of the population doesn’t change over time is also a very peculiar assumption. By allowing different sectors, you can build in more of that richness in how impacts evolve over time.

It also allows you to follow Tom Schelling’s advice. Schelling is, of course, a very prominent economist, and he won the Nobel Prize for his work on game theory. His contributions to the economics of climate change are a bit overlooked. Nordhaus was the first economist to talk about climate change in 1975 or 1977, but Schelling was not far behind; he published in the public literature by 1984.

From very early on, Schelling said that developing countries are much more vulnerable to climate change than developed countries, for the reasons I just gave, but also because of the structure of the economy, access to technology, provision of public goods, and so on.

That immediately implies that there are two ways of reducing the impacts of climate change. One is reducing greenhouse gas emissions, which is the only tool Nordhaus allows. But you could also stimulate economic growth in general, or target particularly vulnerable sectors through targeted development or targeted technological change. That would also reduce climate damages without directly affecting climate change itself.

That is one of the main ways in which FUND differs from other integrated assessment models: we actually include those policy options in the model.

Malaria, public health, and technological change

Richard Tol: That difference has turned out to be important, and reality has borne it out as well. If I think back to the 1990s, one of the things people were terribly worried about was what climate change would do to the spread of tropical diseases like malaria. People were talking about millions of premature deaths per year because of malaria.

That concern has now basically gone away. First Bruce the Younger came with bed nets, then the ban on DDT was reversed, and then Bill Gates funded the development of a malaria vaccine. Malaria is now technically under control. The current problem is that the Trump administration’s attack on foreign aid is reversing some of the progress made under the previous Republican president, but that is probably temporary.

That major concern—malaria—has essentially been reduced by better public health provision and technological progress in medicine. A model like DICE simply can’t do that. It’s not designed to ask that question, whereas FUND is.

Arvid Viaene: There’s also a big point my advisor, Michael Greenstone, makes: like you said, the impacts of extreme heat on mortality are mostly skewed toward the elderly, but especially in countries where there’s less adaptation—less air conditioning, less heating. As income rises, people also have an easier time adapting. Would that be easier to capture in the FUND model?

Richard Tol: Yes. Michael Greenstone, I think, was a co-author on the Deschênes paper with Olivier Deschênes, where they looked at the sensitivity of mortality to heat over a century in the United States and found a secular decline in vulnerability, particularly because of air conditioning, but also because of improvements in healthcare.

Absolutely. FUND is designed to look at those things, and that is, I think, its main selling point.

Arvid Viaene: To be fair, when you describe it that way—and I think I got a presentation by David in Berkeley back in 2015 making this point as well, David Anthoff, your co-author now developing FUND—it made me wonder why Nordhaus or PAGE didn’t take a similar route. It sounds very attractive when you explain it that way.

Calibrating FUND using evidence

Arvid Viaene: On the flip side, what you did sounds very hard, because now you’ve got multiple sectors and have to parameterize or estimate impacts from the literature across different regions and sectors. It’s a much harder problem because you’re breaking it down. How did you go about getting the estimates for the model?

Richard Tol: Essentially, what I now realize—and wish I had realized earlier—is that it’s basically a meta-analysis. You have all these different impacts, and what I did was read the literature, which at the time was still pretty thin, and synthesize from it.

For the impact of climate change on agriculture, there were four or five published studies, and what went into FUND was basically the average of those studies. Similarly for health, there were a handful of studies. In some cases there was only one study, and that’s what I used.

Over time, of course, the literature has thickened—not as much as people think, but definitely more than in the mid-1990s. Recalibrating the model still follows the same principle: what goes into FUND is typically the average and standard deviation of what you find in the literature on a particular impact.

The same is true for the costs of reducing greenhouse gas emissions. What goes in is not some calibrated structural model, but essentially parameters representing the average of what you find in the literature about the cost of reducing methane, CO2, nitrous oxide, and so on.

Arvid Viaene: Maybe I misunderstood, but when you said you wish you had realized this earlier, would that have shaped the model in a different way—as a kind of meta-analysis?

Richard Tol: When I first did this, I didn’t even know meta-analysis existed. It was just what I did. And the literature was so small that there was no need to formalize the process. But as the literature grows, there are more and more studies, and it becomes harder to explain all the choices you make in summarizing the literature.

One of the things I’m currently working on is formalizing that whole process—from the data you find in academic papers to the parameters you find in the integrated assessment model. It’s a statistical problem.

Social cost of carbon meta-analysis and a fast-growing literature

Arvid Viaene: Exactly, because there’s the question of which parameters you use to inform a model. And then you also have a database for the meta-analysis of the social cost of carbon. You have a database including 528 papers on integrated assessment models, which isn’t that many, but a lot of them were published recently. I think almost 10% were published in the last year. Is that because it has become easier? When you started, there weren’t that many studies to pull from, and not that many models. How have you seen the evolution?

Richard Tol: The literature on the social cost of carbon is now very large and growing very rapidly. One of the things I think is wrong in policy advice is relying on a single estimate, because there are so many degrees of freedom and so many things reasonable people can reasonably disagree on. It’s much better to have a panel of experts. But lacking that, one alternative is simply to summarize the literature.

That’s interesting in all sorts of ways. You can detect trends, blind spots, and people parroting each other. All of that is going on in this literature.

When I did my first meta-analysis of the social cost of carbon, it was still a relatively thin literature. At that point, I decided to include all published estimates, or all estimates that seemed to have had some influence on policy. The reason was, first, to increase the sample size so that more interesting statistical analysis could be done.

But second, meta-analysis is well established for data, while a meta-analysis of model outcomes is something quite different. These are not observations sampled from a population; they are outputs of models. Doing statistics on them requires different approaches.

And the main purpose of publishing an estimate of the social cost of carbon is to say: this is what the tax on greenhouse gas emissions should be. So, at that stage, I decided to include republished estimates as well.

If people published a slight variant of the DICE model with a slightly different number, I counted that too. This allowed me to say: well, this is the most prominent model, the most prominent advice. It’s not just Nordhaus saying this—it’s Nordhaus saying the same thing over and over again, and other people picking up his model, making a few tweaks, and publishing essentially the same result. That increases the weight of the policy advice, because it measures pedigree, essentially.

I made that decision back then, and it is now coming back to bite me, because many recent publications simply pick up work by the U.S. EPA, or RFF, or Nordhaus, and say, “I’m going to use this as the best estimate of the social cost of carbon.” That is where much of the growth in the literature is coming from—not necessarily original or independent estimates, but people endorsing previous ones.

Arvid Viaene: Yeah, exactly. It’s like derivations.

Richard Tol: Including a lot of people who miscite previous studies, which is quite intriguing. They say, “I’m going to use Reynolds’s number,” and then use something different.

Arvid Viaene: Yeah, go ahead. Because in that sense, if a lot of people reuse the EPA or RFF or DICE model with some tweaks, then it’s reasonable that you get similar results.

Outro: That was Part 1 of my conversation with Richard Tol. Next week, in Part 2, we move from the structure of FUND to its role in policy — including the social cost of carbon, the Obama-era EPA, and why misunderstood models can be dangerous.

Arvid Viaene: Hi, welcome to another episode of the Climate Economics Podcast with me, your host, Arvid Viaene. Sometimes I come across a paper and I’m really intrigued by its results. Today’s paper is one of those: “Willingness to Pay for Carbon Mitigation: Field Evidence from the Market for Carbon Offsets.”

On this podcast, we’ve already tackled carbon offsets in two other episodes—Episode 4 with Ben Probst, and Episode 17 with Beatriz Granziera. But those were more on the supply side. This paper looks at the demand side: how much people are willing to pay for carbon mitigation.

And importantly, not just what people say they are willing to pay, but what they are actually willing to pay. We’ll also discuss what influences willingness to pay and the field experiment behind these results.

To discuss the paper, I’m delighted to have the author with me: Matthias Rodemeier, Assistant Professor of Finance at Bocconi University. His research sits at the intersection of behavioral economics and public finance, bringing behavioral insights to environmental policy, taxation, and household finance. Many of his studies use field experiments with private and public organizations.

Matthias, welcome to the podcast.

Matthias Rodemeier: Thanks a lot. Thanks for having me.

Arvid Viaene: I was very intrigued when I saw your paper. To start: what’s the number one thing you’d want people to take away from it?

Matthias Rodemeier: The paper studies the market for voluntary carbon mitigation using a field experiment with a large online supermarket in Germany. The supermarket gave consumers the option to compensate the emissions of their delivery. We randomized different features of that option.

What we find is intuitive in one respect: when the offset becomes cheaper for consumers, they buy more—meaning they’re more likely to buy the offset. But when it becomes more impactful—when it mitigates more emissions—nothing happens to demand. People are fully impact-inelastic: they don’t respond to the impact at all. We then explore why this happens and how it can be mitigated.

A final key takeaway is that firm participation matters a lot. If the firm tells consumers it will share part of the cost, people become more willing to buy offsets—and they also become more impact elastic. They start responding to how much emissions the offset actually compensates.

Field Experiment in a German Online Supermarket

How the carbon offset option worked at checkout

Arvid Viaene: Let’s dig into the “price elasticity versus impact inelasticity” result. As I understand it: when prices go down, people buy more offsets—but if you keep price constant and the offset reduces more CO₂, nothing happens. Is that right?

Matthias Rodemeier: Yes. Concretely, this was an online shop where, at checkout, we introduced a box you could click that said: “I would like to mitigate the emissions of a typical delivery.”

That could be, say, two kilograms of CO₂—that’s the “impact” attribute. The other attribute is what it costs—maybe €0.20, €0.40, €0.60, or €1.00.

We randomized both attributes: the price and the impact. Impact could be 2 kg, 4 kg, or 8 kg of CO₂, for example. What we see is that varying impact does absolutely nothing to demand. People buy just as much whether the offset compensates 8 kg or 2 kg.

That’s striking. A market analogy would be: if I sell you one Snickers bar or four Snickers bars for the same price, you’d normally care. Here, people either struggle to understand what they’re buying—or they don’t care.

Key Result: Price Elastic, Impact Inelastic

Warm glow vs valuing real mitigation

Arvid Viaene: That suggests people buy offsets for reasons other than mitigation.

Matthias Rodemeier: The classic interpretation—often discussed as “scope insensitivity”—goes back to early work by Kahneman and Knetsch, and also relates to Andreoni’s, “warm glow” idea.

Warm glow means: people do something good to feel good, but they don’t really care how good it is or how much impact it has. They’re still price elastic—if doing good becomes cheaper, they do more. But if doing good becomes more impactful, they don’t respond. They just want the warm feeling.

Arvid Viaene: So they buy more because they can get more of the warm feeling when it’s cheaper, but the impact itself doesn’t matter.

Matthias Rodemeier: That’s the classic warm glow interpretation, yes. And then we test whether it’s really warm glow—or whether people just don’t understand the impact dimension.

Learning Effects: People Start Valuing Impact Over Time

Arvid Viaene: You tried to separate intrinsic valuation from warm glow, right?

Matthias Rodemeier: Yes. A key feature is that we didn’t only randomize impact between people; we also randomized it within the same person over time. The same customer might visit the website multiple times, and across visits they see different impact levels. That allows learning, because “2 kg of CO₂” versus “4 kg” is not intuitive for most people. People don’t naturally know what those magnitudes mean.

But if today you see 4 kg and yesterday you saw 2 kg, you can at least infer: “This is twice as much as before.” If demand starts responding over time, that suggests people weren’t purely warm-glow-driven—they were also struggling to evaluate the product. And that’s what we see: with experience, people start becoming more responsive to impact.

How Much Do People Actually Pay per Ton of CO₂?

Arvid Viaene: You transform the experiment’s units into the standard “euros per ton of CO₂.” What magnitudes do you find?

Matthias Rodemeier: If you only look across people (ignoring learning), you’d conclude willingness to pay for the mitigated carbon is basically zero—people buy offsets, but not because of mitigation.

But once you allow for learning through repeated exposure, people start being more likely to purchase when the offset has higher impact. Then we estimate willingness to pay of about €13–€16 per ton of CO₂.

That’s still far below common estimates of the social cost of carbon, and below many policy carbon prices. So even after learning, voluntary markets do not come close to fully internalizing the climate externality.But it quantifies how far away this private market is from the social cost of carbon.

Arvid Viaene: For reference, the EU ETS is much higher than that. And some social cost estimates go far higher too.

So if I understand correctly: at first, people might mostly be buying for warm glow, but over time they learn what the impact means—and then they start buying partly for actual reductions.

Matthias Rodemeier: They may still buy for warm glow—the warm glow doesn’t necessarily disappear. But as they learn the magnitudes, they start valuing impact as well. They begin to choose offsets that have higher mitigation impact.

Arvid Viaene: Did you also estimate warm glow in comparable units?

Matthias Rodemeier: Yes. If you decompose it: the intrinsic willingness to pay is about €13 per ton of CO₂. Warm glow is about €1. And if the firm chips in, that adds about €2 more. That’s how you get up to around €16 per ton in our highest estimates.

Firm Participation Changes Demand and Impact Sensitivity

Subsidies vs matching contributions

Arvid Viaene: Let’s talk about the role of firms. You looked at both subsidies and matching, right?

Matthias Rodemeier: Exactly. We randomized whether the firm told consumers it would pay a share of the offset cost. A subsidy looks like: “This offset normally costs 40 cents, but we as the firm will chip in 50%, so you only pay 20 cents.” Alternatively, the firm could do a match: not making it cheaper, but increasing the amount of carbon mitigated. For example: “If you offset 2 kg, we’ll offset another 2 kg at our expense.”

We compare these in terms of cost-effectiveness. If you’re a firm deciding where to spend your next euro—on a subsidy or on a match—you want to go for the match. Offsets are price elastic, but not extremely so. With a subsidy, additional mitigation mostly comes from marginal consumers who buy only because the price dropped.

With a match, everyone’s purchase becomes more effective—including the people who would have bought anyway. That makes matching much more cost-effective than subsidizing the price.

Arvid Viaene: So the match is better because the subsidy doesn’t bring in that many new buyers, whereas the match increases mitigation across the board.

Matthias Rodemeier: Exactly.

Surveys vs Real Choices: The Hypothetical Bias Gap

Arvid Viaene: Another part of the paper is that you also surveyed people about what they were willing to pay.

Matthias Rodemeier: Yes. There’s a huge literature in environmental economics estimating willingness to pay through surveys—contingent valuation. Historically, economists used surveys because there was no way to incentivize these choices—no real market. The market for carbon offsets gives us an opportunity to observe real behavior and estimate willingness to pay from revealed preferences.

But we also wanted to know: if we had done it the “old school” way—asking people in a survey—would we get the same results? So after the field experiment, we invited some consumers to a survey and asked them, hypothetically, what they would be willing to pay for the same offset product.

The numbers were more than an order of magnitude larger. Survey respondents were willing to pay over €200 per ton of CO₂ on average, compared to about €13 per ton revealed by choices. That’s exactly why field experiments matter: what people do can differ enormously from what they say.

Arvid Viaene: Do you have a sense of why the gap is so large?

Matthias Rodemeier: We designed the survey carefully to be apples-to-apples: we asked about the same offset product, not about policy instruments like carbon taxes. Even then, the gap remains.

This is consistent with a big literature on hypothetical bias—including work by John List. People tend to overstate generosity in surveys. There’s also social desirability bias: people want to look good when answering. And even without intentional misrepresentation, it’s hard to predict what you would do in a real market context. “Talk is cheap,” as economists like to say.

How the Experiment Got Started

Arvid Viaene: How did you go about setting up this experiment? You reached 250,000 consumers with one of the largest online supermarkets—so how did you get it off the ground?

Matthias Rodemeier: I’ve been running field experiments with firms for quite a long time—I started doing this at the outset of my PhD.

One thing that surprised me early on was how long these projects can take. Sometimes it’s years from the first contact with a firm until you actually run the experiment. In this case, it was much more efficient. The company was very open to testing these kinds of strategies.

Part of the reason is that they’re in a booming industry right now—home delivery. Whether it’s Amazon, grocery delivery, fast food delivery—everything comes to your door now. And of course, that produces emissions that consumers might worry about, especially in European cities where the alternative is often to walk to the supermarket or take a bike.

So it was somewhat natural for this firm to think about carbon offsetting and other mitigation strategies. The way we started was actually pretty simple: I kept seeing their trucks driving around everywhere in my city.

At some point I picked up the phone, tried to figure out who the CEO was, and talked to him about why they weren’t offering carbon offsets—and whether this could be something we could do together. And they were very excited.

Arvid Viaene: Awesome. That’s the entrepreneurial mindset you need for field experiments—someone has to get it moving. And as I read it, you did the experiment in 2020, and it’s only now published—so congratulations.

Matthias Rodemeier: Yeah—these things take a lot of time.

Arvid Viaene: It takes a long time. From the experiment to publication, five years.

Matthias Rodemeier: Yeah. Welcome to academia.

What comes next in research

Arvid Viaene: Have you done further work in this field? Are there new working papers or projects building on this?

Matthias Rodemeier: I’ve been talking with various firms to study the market for carbon offsets further. I’m also partnering with a firm that installs cookstoves in Tanzania and tracks emissions through digital trackers. We’re about to run field experiments there as well. I’m also talking with companies that offer offsetting for events they organize. This has become something I’m really interested in.

It takes time—there’s always a lag. But I’ve been encouraged. Since the paper came out, a lot of people have talked to me about related ideas. A lot of PhD students I’ve met are working on carbon offsetting now—trying to understand what drives willingness to pay for carbon mitigation. It’s a growing field, especially at the intersection of behavioral and environmental economics, and I’m getting excited about it.

And we’re going to do much more on this—but you’ll probably have to wait another five years for it to get published.

What the results imply for climate policy

Arvid Viaene: In the paper, you write that the €13 intrinsic value suggests voluntary climate protection initiatives may internalize only a small fraction of climate externalities, which has implications for environmental policy. What’s your takeaway there?

Matthias Rodemeier: I think there are two issues. One we pay a lot of attention to in the paper is trust. We don’t know ex ante how much people trust these offsets. One reason we observe willingness to pay that isn’t terribly high is that people have a lot of distrust in this market.

And a lot of distrust is justified because it’s a market with a lot of adverse selection. We took a long time choosing an offset that was a high-quality one, but people may still distrust the market. And we have some evidence in the paper that this is part of the story.

Now, regarding the €13 estimate: I think it tells us that given the current market environment—which may include distrust and adverse selection—this is what the private market can currently do in terms of mitigating the externality from consumption.

And I think it tells us that this market can really only be a complement in a world with imperfect environmental policy. But it can certainly not be a substitute. We cannot think of this market as something that can replace important regulation. We need environmental regulation—cap-and-trade or carbon pricing—to get to what economists call the first best: internalizing the externalities from emissions.

Quantifying willingness to pay in this market is informative because it quantifies the gap between what we think the social cost of carbon is and what people voluntarily are willing to pay.

Arvid Viaene: That makes sense. Complement, not substitute—and the gap is informative.

Matthias Rodemeier: One thing I should add is that the way we estimate willingness to pay actually takes care of much of the distrust. Broadly speaking, we look at how demand responds to price chxanges and to impact changes, and we use that relationship to estimate willingness to pay. To some extent, distrust “washes out” in those estimates. We show that more formally in the paper—there’s a long appendix on that if anyone feels unconvinced.

Arvid Viaene: That’s good.

Matthias Rodemeier: We say only referee two reads the appendix.

Arvid Viaene: Yeah, exactly.

Market integrity and greenwashing risk

Arvid Viaene: Is there anything we haven’t talked about that you’d like to highlight?

Matthias Rodemeier: I think we covered the important parts. Maybe one thing I should really highlight is that this market is growing rapidly and becoming more important. The finding that—without additional learning and help—consumers seem to be fully unresponsive to how impactful these carbon offsets are is quite concerning. Because not only do we have adverse selection on the supply side, as you discussed in other podcast episodes, but we also find that on the demand side, consumers have a hard time telling apart a low-impact offset from a high-impact one. That’s concerning because it suggests even more incentives for firms to greenwash: to offer something that looks good, but doesn’t really have much impact. So I think we need to think hard about solutions that help consumers make better decisions.

Closing

Arvid Viaene: Awesome. Thank you so much, Matthias, for taking the time. I really appreciate it.

Matthias Rodemeier: Thanks for having me.

Transcript

Arvid Viaene: Hi and welcome back to Climate Economics. I’m Arvid Viaene.

In the last episode, we talked about the EU’s Carbon Border Adjustment Mechanism. In particular, we discussed the following big-picture question: what are the global impacts of the Carbon Border adjustment Mechanism—who gains, who loses, and what it means for consumers and firms.
We discussed both theory and estimates. And I recommend checking out that episode if you want a good overview of the global effects.

Now, I think overall that this border adjument mechanism is a really good one. But here’s the reality: a good idea on paper can still fail in practice—or at least create a lot of friction—if implementation is messy. And with CBAM, implementation is definitely challenging.

Because CBAM is trying to do something incredibly ambitious: it is trying to copy the logic of the EU ETS beyond Europe.
Because the EU ETS prices emissions at the level of an installation—a plant. And to do that, it has developed a system where monitoring and verification have been built up over years. However, CBAM is different. For CBAM, the EU has to price emissions in a product coming into the EU. And that product may pass through multiple tiers of suppliers and in multiple countries. So that shift—from plant-level pricing to product-level accounting—sounds subtle, but it changes everything.

It raises practical questions like: what counts as “embedded emissions” for a specific shipment? And how can monitoring and verification work? In addition, and in the situation where companies don’t have this data, they have to resort to default values set by the EU. But how are those set and how high are they? And what kinds of uncertainty does this create for firms trying to plan, budget, and stay compliant?

Those are the questions we will tackle in this episode. By the end, you’ll have a clear mental model for default values versus reported emissions, a sense of the difficulties of reporting and verification, and a practical map of the upcoming milestones and remaining open questions that matter most for companies.

And to unpack all of this, I’m joined by Pauline Miquel, a policy expert working directly on CBAM implementation.

Pauline’s work focuses on monitoring regulatory evolutions across jurisdictions, external affairs, and public-facing content creation. She holds a dual master’s in environmental economics and climate change from PKU and LSE, with research focused on CBAM implications for the steel industry. Previously, she worked as a corporate sustainability project manager in steel supply chains. Pauline, welcome to the podcast.

Pauline Miquel: Thank you. Thanks for having me.

Expected costs of CBAM likely are much higher for importers

Arvid Viaene: I generally ask guests this first: what is the number one thing you want people to take away about CBAM and what’s happening right now?

Pauline Miquel: In the context of CBAM right now—at the end of 2025—we’ve seen lots of changes in terms of how the policy will actually look when it goes live in 2026, especially around the magnitude of the cost for different products.

One key thing people should know is that we expected costs to be much lower than what has finally been decided by the Commission, in a very last-minute move in mid-December. For most importers—if they rely on what we call “default values” (and I’m sure we’ll get into the details)—CBAM charges will be much higher than they expected until now.

Arvid Viaene: Can you speak more about that? What happened that it’s suddenly more expensive than expected? They changed those values?

Pauline Miquel: The short answer is: they never published those values until the 17th of December. And yes—that’s the kind of reaction we get when we say this, but it’s true. There was a lot of information leaked throughout the process of determining those values, so we had hints about what they might look like. But ultimately, we only knew the exact values last week—from the 17th of December.

How CBAM works in practice: coverage, supply chains, data, and default values

Arvid Viaene: We’ll come back to that, but first: which industries are covered by CBAM?

Pauline Miquel: There are six industries covered initially. These are the most emissions-intensive sectors in the ETS, and also the sectors the Commission thinks are most exposed to carbon leakage.

The industries are: cement, steel, aluminum, hydrogen, electricity, and fertilizers.

Within those industries, you have a list of customs codes—what we call CN codes—that are covered. So it’s very specific in terms of which products are covered.

It’s also worth specifying that it’s supposed to cover mostly raw materials—say, a ton of raw steel. But it also goes down to some more finished or semi-finished goods. You have things like screws, fasteners, nuts, and bolts that are already covered by CBAM.

So it’s starting to go into some downstream products already.

Arvid Viaene: The big challenge, as I see it, is that it took a long while to get the EU ETS set up and running. In my conversation with Jos Delbeke, he said there was a long period where they tried to get the statistics. But we don’t have those statistics for foreign firms.Ideally, firms use their own values, but then there are “default values.” Can you explain how this will work for producers?

Pauline Miquel: The policy was designed with a transitional period from 2023 to 2025—which we’re reaching the end of now—where importers could declare emissions values quarterly without facing the financial charge CBAM introduces. It was meant to be a trial phase.

Internally, we think this transitional phase was almost wasted, because no real enforcement happened. Not the financial charges of CBAM, but even the penalties that were supposed to be imposed on importers misdeclaring emissions—those weren’t applied.

So the data collection hasn’t necessarily been very good. And the core principle behind CBAM is that importers collect a lot of information from their supply chains—several tiers, up to the raw material producers. That’s very difficult for companies that weren’t used to doing this before, especially importers who were not facing the ETS at all—which is most CBAM declarants.

There’s been a huge need for education, and that’s part of what my company has been doing for the past two years.

But whether values were correct—we have no idea, because nothing has been verified or enforced properly. A lot of companies might not have declared anything. We don’t really know. The Commission knows, but there’s very little published information. There is a report that was published recently showing some numbers, but it’s still broad.

Now, another issue with the transitional phase is that the default values—the emissions data, the emission factors—were all for the transitional phase only.

Arvid Viaene: When you say “default values,” that’s like: if a company doesn’t use its own values, it defaults back to some number the Commission proposed, right?

Pauline Miquel: Exactly. There was a list of values used in the transitional period—but it was always going to be the list for the transitional phase.

In the definitive period of CBAM, which starts next week, there is a new list of values—the final list. And again, we only saw it last week.

The default values essentially determine cost for importers, because we’re multiplying embedded emissions by the price of carbon. The formula is more complex, but as a simplified explanation, that’s the idea.

Arvid Viaene: Right—say you get two tons of CO₂ per ton of steel, and an ETS price of €60 per ton. Multiply them, and it’s €120 per ton of steel.

Pauline Miquel: That’s a very simplified explanation, but it’s the broad idea. We’re basically imposing the EU carbon price onto imports. But we first need to know what the emissions are in the imported product. In the EU ETS, we price carbon based on emissions of an installation—a plant or factory. With imports, we’re talking about a product. That’s a major difference between ETS and CBAM. We’re trying to replicate what is done with ETS onto manufactured goods—which involves far more information from different tiers in the supply chain.

Why default values are punitive (and why that matters)

Arvid Viaene: I’ve read that the Commission’s default values are based on the most polluting firms, to create an incentive for importing firms to declare actual emissions. Is that right?

Pauline Miquel: Yes. One defining principle is to encourage supply-chain data collection—to map emissions intensity globally—and reward best-in-class producers. That’s also what makes it a climate policy and not a trade policy. The Commission portrays CBAM as a climate tool, not a trade barrier—and in the global geopolitical context, that matters.

So there’s a list of default values—emission factors—that say, for example, “one ton of steel produced in China emits X tons of carbon.” It’s done at the country level and per product, tied to CN codes.

Those default values apply if there is no actual data being collected from the supply chain. To maintain the incentive, the Commission had to come up with values that represent a worst-case scenario. Technically on paper, they’re supposed to reflect a country average, and then there is a markup—a punitive element—added on top.

Arvid Viaene: So is it based on China’s average, or the worst producers in Europe?

Pauline Miquel: It’s per country, so it should be the average in China—but that’s the part we’re somewhat unsure about. Did they use worst producers in China? An average? Or did they just listen to EU industry lobbying for a high value? Technically, it’s supposed to be a country average, and then in order to make it punitive, a markup is added to ensure it’s higher than what you’d get if you collect actual data.

Arvid Viaene: And is the cost increase you mentioned earlier because the final default values are higher than the transition values?

Pauline Miquel: Absolutely. In the transitional period, the values were not country-level. They were an average emissions intensity for production outside the EU, per product. That was much easier to work with. But it wasn’t really reflective of the world’s diversity in production routes and emissions performance. So transitional CBAM was a simplified version.

Can countries contest the default values?

Arvid Viaene: Can countries or industries contest those default values?

Pauline Miquel: There is no formal channel for the Commission to get feedback from other countries. The Commission is working with trading partners to fine-tune the policy, but those values are supposedly final for 2026—they won’t change for the first year.

They will be reviewed in 2027. That’s something we learned recently—because there is uncertainty about the values. The values were kind of rushed. I assume feedback from industry, countries, and others will be taken into account, but what that means in practice is hard to say.

Arvid Viaene: And the big change is: transitional phase was one average per product, and now it’s per product per country—so big differences.

Pauline Miquel: Exactly. And in 2026, the punitive markup is 10% the first year. It goes up to 20% in 2027, and from 2028 onwards it will be 30%.

Arvid Viaene: That could have a huge impact.

Pauline Miquel: It does. For example, steel from Indonesia—in the 2026 list—is quantified at nine tons of CO₂ per ton of steel. It’s extremely high.

Arvid Viaene: So you would add 30% on top of that. And what’s the average in Europe?

Pauline Miquel: About 1.5 to 2.

Arvid Viaene: Yes, that is a big difference

Verification: the “ETS logic,” but globally

Arvid Viaene: CBAM is trying to incentivize firms to use actual emissions. What determines whether reported numbers are acceptable?

Pauline Miquel: In the transitional phase, there was no real threshold—it wasn’t monitored. It was about the exercise of getting information into quarterly reports, and helping the Commission identify hotspots and administrative burden.

In the definitive period, a verification mechanism is introduced. Reported values need to be verified by a third-party auditor—similar to the ETS. In the ETS, installations in Europe are audited so their numbers can determine how many permits they need. With CBAM, the EU wants CBAM to mirror the ETS: a replica of the ETS on trade. But in practice it’s a whole different level of complexity: you’re sending auditors around the world, auditing emissions in many countries with different contexts and political structures. And for one imported good—especially in steel, where supply chains are fragmented—you might need auditing for multiple installations from raw material to manufactured product.

Arvid Viaene: That sounds like a gigantic undertaking. Because there are only so many resources and know-how available. Because with Jos Delbeke, we did not even talk abouth the verification part.

Pauline Miquel: Yes. These are the details that people were probably amazed by, if not completely shocked by, at the beginning of EU ETS. But now people take just take it as given.

A major uncertainty: costs, timing, and the “omnibus” simplifications

Arvid Viaene: What additional sources of uncertainty are there for importers?

Pauline Miquel: The verification process is very theoretical right now. There’s huge uncertainty in how it will work in practice. Verification is required before values can be used to determine how many CBAM certificates are needed—so, how much CBAM costs.

But in the first year there’s a particular regime. Emissions from 2026 determine cost—but you need the full year of carbon accounting before a verifier can certify the values. That makes it very challenging for importers to predict their CBAM liability.

Even the best-prepared importers—who engaged suppliers for two years—still can’t be sure their numbers are correct. Suppliers may overlook parts of carbon intensity. And because transitional values weren’t enforced, it’s hard to rely on those data to predict the future.

If you decide, “To be safe, we’ll rely on default values in 2026,” then the cost becomes huge for most importers—especially because a lot of affected volumes are imported from Asia, with higher carbon intensity (particularly steel and aluminum).

Another complication: the financial cost of CBAM has been postponed to 2027 through the simplification reform—often referred to as the omnibus—introduced in February and formally adopted in October 2025.

The main CBAM simplification is that the threshold was changed from €150 worth of goods to 50 tons of annual imports as the minimum threshold for CBAM to apply.

Another, more subtle change is that the Commission decided to start the sale of CBAM certificates—so the actual financial liability—in 2027. Importers can only start purchasing CBAM certificates from February 2027. So the year 2026 is almost like walking in the dark: there is an invisible liability. Also, reporting used to be quarterly; it will now be annual. The 2026 emissions report is due in September 2027.

Arvid Viaene: That’s a lot of uncertainty—prediction, readjusting, and updating.

Pauline Miquel: Exactly.

What CBAMBOO does (and why companies are struggling)

Arvid Viaene: I looked at your site. Could you share what CBAMBOO does to support companies through this uncertainty?

Pauline Miquel: The company was set up in 2023 by the two co-founders, Gabriel Rosenberg and Daniel Sharpe. The idea was to build digital tools to manage this new trade problem from an importer’s perspective—by building a database of emissions information from suppliers worldwide, linked to European importing companies.

CBAM is largely about data sharing. CBAMBOO built software that helps importers collect information from suppliers by onboarding suppliers onto a platform where they can create a profile with emissions intensity for different products. There’s a network effect: that information can be shared with other European customers who need it.

Originally, it was a software alternative to the Commission’s proposed system—a bunch of spreadsheets. The Excel template was changing every month, and it was meant to be emailed back and forth across many companies, then uploaded into the EU registry. The founders thought: this system will break. We need a more rigorous IT infrastructure.

Now the company has evolved into a companion for any importer taking CBAM seriously: the software supports information flow, but we also support importers in tracking changes and understanding where things are going.

A lot of businesses in Europe are left behind. They don’t understand how much they’ll have to pay, where to get emissions data, how to engage suppliers, or how to educate suppliers. Sometimes we step in and talk to suppliers directly to explain what information they need to provide—because the Commission created a unique methodology instead of using an ISO standard.

We’ve also tried to educate companies to treat CBAM as a business process, not just a reporting mandate. During the transitional period, some companies treated it like a sustainability reporting obligation: report and you’re done.

But CBAM reporting was meant to prepare companies for the fact that the information they collect determines their bill. They will need to buy tradable certificates. So they got used to reporting it, but not realizing it will be used for the financial payments. So it becomes a whole new business practice—like ETS.

And we go further: how do you price this for your own customers? How do you pass costs downstream? How do you reflect it in supplier contracts? How do you involve finance teams? How do you train procurement?

Arvid Viaene: Because procurement decisions used to be quality and price. Now you have to integrate carbon intensity too.

Pauline Miquel: Exactly. Different supplier profiles emerge. To compare suppliers—even within the same country—you need emissions information integrated into your business processes and systems, like your ERP.

Are suppliers outside the EU preparing?

Arvid Viaene: Are you seeing suppliers abroad get ready to provide this information?

Pauline Miquel: Yes. The largest companies, especially those dependent on the European market, are trying to get ready. It’s been challenging for suppliers abroad too—they’re not simply trying to get around the system as you sometimes hear in the EU. Many are trying to understand how to turn this into an advantage.

But it’s not obvious how to calculate emissions, and suppliers don’t necessarily have easy access to Commission information. If EU importers are lost, imagine suppliers in China.

Still, especially among companies we work with, many are trying to get this right. In China, firms are trying to turn it into an opportunity—setting up emissions monitoring systems. They’re starting to understand that carbon is becoming a new competitive advantage.

And in that sense, from a policy perspective, CBAM has good prospects. I think it can have a very positive impact—but it will take time to implement properly, like the ETS. It’s just a next level of complexity.

One more technical point: the benchmark (and why it matters)

Arvid Viaene: Is there anything else we haven’t discussed that you want to mention?

Pauline Miquel: One critical aspect is the formula. It’s not as straightforward as “emissions times carbon price.” There are about five variables, including a key one: the benchmark.

The benchmark is supposed to reflect the level of free allocations that EU producers of the same good still benefit from under the ETS. If CBAM priced carbon at the border in full, without reflecting free allocations in the EU, then it wouldn’t be fair. So CBAM takes that into account. The benchmark is something deducted from embedded emissions, set at a level supposedly reflecting best performance in the EU.This is important because it determines the cost too. Lower benchmarks mean higher costs—it’s an inverse relationship. And similarly to the default values, we received these benchmarks only last week.

Arvid Viaene: That seems to be a theme. I actually lost track of the updates. All of these have come in the past for

Pauline Miquel: Yes—for 2026. And then in 2027, it’s back on the table.

Closing Remarks

Arvid Viaene: How do you keep track of all of this?

Pauline Miquel: It’s hard. The EU policymaking process is transparent on paper, but there’s a lot behind the scenes. It helps to connect with people who understand lobbying dynamics and the policymaking process in Brussels—and to track changes across websites constantly.

Arvid Viaene: Pauline, thanks so much for taking the time. This conversation really shows how much uncertainty is involved, and how much practical detail matters. Thanks again.

Pauline Miquel: Of course. Thank you so much for having me.

Arvid Viaene: Thank you.

That is why I was excited to discuss Kimberly’s paper “The Global Effects of CBAM”, which aims to quantify the costs and benefits of CBAM, both for the EU and globally, as well as for consumers and producers.

I think this article is a great gateway into understanding the big-picture mechanisms and effects of CBAM.

Transcript

Arvid Viaene: So, welcome to another episode of Climate Economics with your host Arvid Viaene. Climate change has an inherent free rider problem because individual countries bear the costs of their domestic carbon regulation, while the benefits of reducing CO2 are shared globally.

To solve the free rider problem, the European Union has introduced a carbon border adjustment mechanism, which came into effect this year. With this mechanism, the EU wants to address this free rider problem.

The idea is that you impose a carbon tax on importing firms similar to those on the domestic firms. As a result, you can improve domestic competitiveness, reduce emission leakage, and encourage other countries to tax carbon.

Now, those are great goals in principle, but what are the estimated effects in practice? That is the topic of today’s discussion, based on a paper called The Global Effects of Carbon Border Adjustment Mechanisms.

I think it’s an amazing paper which tackles all of these topics. In addition, this paper also analyzes the worry expressed by the European Union that CBAM could have a larger impact on lower-income countries.

Arvid Viaene: To discuss this paper, I’m delighted to have one of its authors with me today, namely Kim Clausing. Kim is the Eric M. Zolt Chair in Tax Law and Policy at UCLA School of Law, and a non-resident senior fellow at the Peterson Institute for International Economics, as well as a research associate at the National Bureau of Economic Research.

During the early Biden administration, she served as Deputy Assistant Secretary for Tax Analysis at the United States Department of the Treasury, acting as the lead economist in the Office of Tax Policy.

Arvid Viaene: Her work focuses on how government policy and corporate behavior interact in the global economy, with publications on taxation, international trade, and climate policy. So Kim, welcome to the podcast.

Kim Clausing: Thanks so much for having me.

What CBAM is and why it matters

Arvid Viaene: CBAM is one of the most exciting developments taking place right now in climate economics. I gave a brief introduction already, but would you mind explaining what the carbon border adjustment mechanism is and why you decided to study it?

Kim Clausing: Absolutely. I agree with you that it’s one of the most exciting things happening in climate policy. What’s really great about the CBAM is it provides an answer to the free rider problem, as you described it, because it makes it easier for countries to adopt ambitious climate policies, and it also makes it easier to facilitate climate action abroad.

Let me explain how it works. Imagine you’re in Europe and there’s an emissions trading system. Because you are phasing out the free allowances, your firms are now facing more and more costs associated with their carbon emissions.

That puts your firms at a disadvantage relative to firms in other countries. You’d worry that consumers might substitute goods that are dirtier than the domestically produced goods. What a carbon border adjustment mechanism does is simply negate that self-imposed competitiveness disadvantage. So it’s not protectionist; it’s more re-leveling the playing field after you’ve harmed your own producers by making them internalize this carbon cost.

A nice feature of the EU carbon border adjustment mechanism is it also provides a credit if other countries have imposed carbon prices of their own. So imagine Indonesia has a carbon price equivalent of 20 euro and the European Union has a carbon price equivalent of 80 euro. Then the difference of 60 euro would be the border adjustment mechanism, but they’d get credit for having a carbon price of their own.

Kim Clausing: This policy can handle three important goals:

1. addressing the leakage problem of people substituting for dirtier sources of production—or even moving production to lightly regulated jurisdictions;

2. facilitating carbon price adoption at home, because it has an answer to that competitiveness problem; and

3. facilitating carbon price adoption abroad, because countries can convert foreign tariff revenue into domestic revenue and achieve some of their own climate policy goals.

Source: https://asuene.com/us/blog/cbam-the-eus-carbon-border-adjustment-mechanism-and-its-latest-developments

Stylized fact I: Carbon pricing and competitiveness

Arvid Viaene: Thank you. Maybe we can start with some of the stylized facts you have in your paper, because I read some of those and I was surprised by some of your results. They provide a nice framework to talk about your results.

Arvid Viaene: The first stylized fact, or question, is: how does carbon pricing affect competitiveness? Could you talk about that?

Kim Clausing: Yes. Carbon pricing raises costs for your domestic firms. That’s going to harm their competitiveness absent some sort of carbon border adjustment mechanism. What the carbon border adjustment mechanism does is subject foreign producers to your carbon price should they be serving your market. It doesn’t really address the export problem, and that’s part of why it’s important to also incentivize action abroad.

Let’s say you’re a German firm and you’re subject to the European price. You can rest assured that in Europe, foreign firms will be subject to that too. But that doesn’t mean you’ll be on a level playing field when you’re both trying to serve a third market abroad.

So it’s also important to think about how to facilitate more and more carbon price adoption throughout the world if you want to handle the worldwide competitiveness problem. But at least the carbon border adjustment mechanism can solve the domestic competitiveness problem.

Arvid Viaene: Exactly. It’s like leveling the playing field domestically, but internationally it will remain different.

Kim Clausing: Exactly.

Source: https://www.fertilizerseurope.com/fitfor55-ets-cbam/

Surprising Results on emissions intensity and lower-income countries

Arvid Viaene: One thing I was surprised by is you look at how carbon pricing affects producers in lower-income countries. The story you often hear is that there might be emission leakage and companies might move abroad where environmental regulations are less stringent, so emissions would go up. You look at emissions intensity for those countries. Could you talk about that?

Kim Clausing: Yes, absolutely. We were somewhat surprised by this finding that there wasn’t a correlation between income per capita in countries and their emissions intensity.

I think a lot of people going into this thought, “It’s probably the case that poorer countries have dirtier production, and so this would disproportionately harm them.”

Kim Clausing: Many early observers also made the mistake of not thinking through the true incidence of the carbon border adjustment mechanism. It’s not so much that it’s harming poor countries if they’re sending goods to Europe, because the European price will be higher because of carbon pricing—and the border adjustment mechanism is just undoing an advantage that they would otherwise be handing to the rest of the world.

Kim Clausing: There are two misconceptions here. One is the incidence question of who’s really bearing the burden of this policy. The second is which firms will win and lose under this scenario.

Kim Clausing: Europe’s going to have a higher price for goods like aluminum and steel. So selling to Europe comes with a premium. Those firms that are particularly green will, on net, benefit because they’ll get a higher price, but their carbon fee won’t be enough to offset the benefits of that high price.

Arvid Viaene: All right.

Kim Clausing: Whereas the dirty firms may find that this is bad for them because they’re so carbon intensive that, if they did serve Europe, they would have to face a high fee. They might end up reallocating their exports to other markets that aren’t regulated, but then the prices in those markets will be driven down by the increase in supply. So you get this tale of two types of firms where the clean ones may actually benefit and the dirty ones are harmed. It becomes really important which firms are clean and which are dirty.

One thing we find, using detailed plant-level data on every aluminum smelter in the world and most steel plants in the world, is that there isn’t a tight correlation between GDP per capita and emissions intensity.This is true even if you control for variables you might think matter, like scale, foreign ownership, and the like. That was surprising to us. But it’s an encouraging message for the EU because they can implement this policy without worrying that it’s going to have disproportionately negative effects on the poor countries of the world—who are suffering disproportionately from climate change because of where they’re located.

Arvid Viaene: Yeah. Rephrasing that: there’s also a lot of very efficient firms abroad that are not often captured in this story. So people say there’s going to be a disproportional burden, but those countries also have very efficient firms that don’t emit a lot. That’s something I really learned.

Why steel and aluminum, and what data the paper uses

Arvid Viaene: That’s a good transition to talk about the two industries you study. You mentioned aluminum and you mentioned steel. Could you talk about why you chose those industries?

Kim Clausing: Yes. The European Union CBAM was the policy instrument we were interested in looking at, and it applies to other industries as well. It applies to aluminum and steel, and those are the two we focus on, but also fertilizers, cement, hydrogen, and electricity. If you look at all of those industries, aluminum and steel—and we use steel broadly to include both iron and steel—are the two industries that are both emissions intensive and highly traded.

Together, those metals account for about 14% of the world’s carbon emissions if you include scope one—not just the production process emissions, but also the electricity emissions used in production. That’s a lot.

If you look at those other industries, aside from electricity, they’re less important emissions-wise, and they’re also less traded. Cement is very important emissions-wise, but isn’t traded. Fertilizer is less important emissions-wise, even though it is traded.

But these two industries are both highly traded and very emissions intensive. In steel, more than 20% of output is exported; in aluminum, more than 40% of output is exported.

Arvid Viaene: It seems like it was also a very big data undertaking to get all this data. People might not appreciate the scope—could you talk about that?

Kim Clausing: Once we identified those industries as most important, we found very detailed data on production and emissions. In the aluminum sector, we have data from every smelter in the world, acquired from Wood Mackenzie. The steel data are from Climate Trace, and they’re also at the plant level.

This level of detail really helps the analysis because we get much more precise estimates of how markets are going to react to carbon pricing in the CBAM, accounting for heterogeneity. Firms vary in important dimensions—not just emissions intensity (and there’s a lot of variation there), but in other dimensions as well. This happens both across countries and within countries.

Within China, for instance, some firms are much sturdier than others, and that’s true for a lot of countries. You want to account for what’s going on at the plant level as well as at the country level.

Arvid Viaene: I should also mention there’s some really good econometrics in the paper, which is not going to be today’s discussion, but I really recommend it. It was interesting econometrics and identification.

Kim Clausing: Thank you.

Baseline scenario: $100 carbon tax with and without CBAM

Arvid Viaene: I usually skip that because I just assume it works, but for people interested, I recommend it. Maybe we can talk about some of the results. Your baseline analysis starts from a $100 carbon tax, where you analyze the world with and without the carbon border adjustment mechanism. Could you talk us through some of the results?

Kim Clausing: Sure. When you’re thinking about the tax all by itself, it shouldn’t surprise economists that taxes reduce consumer and producer surplus and raise government revenue. That’s a second-week-of–Econ-101 result, and that happens here too. One thing that was a little surprising is the magnitudes aren’t huge. When you look at overall welfare effects of implementing carbon pricing, with and without the CBAM, globally it’s not moving the dial very much. We get numbers like a billion dollars, and you wonder, since not that much is happening quantitatively, why these policies are so hard to do. But the policy analysis also tells you why. Producers do get hurt by carbon pricing and can be expected to object.

One interesting thing about the carbon border adjustment mechanism is it reduces the producer surplus losses. It doesn’t eliminate them, but it makes the tax a little easier for producers. The cost of that is imposing more of a burden on consumers because, without the border adjustment mechanism, some consumer pain is ameliorated by imports that come in and offset higher prices that would otherwise occur.

So the border adjustment mechanism creates a mini redistribution away from consumers in the country doing the policy and toward producers. Government revenue is substantial, but mostly from the pricing. You’re not getting a lot of revenue out of the CBAM itself. But what the CBAM is doing is making it easier to carbon price in the first place. You see that in the results: the countries implementing the CBAM will find it’s net helpful to them relative to a situation without a CBAM. Again, though, the magnitudes are not enormous.

Arvid Viaene: And when you said “easier to implement,” that’s maybe because the objections from industry might be a little less.

Kim Clausing: Yes. And the welfare effects are just a tiny bit less bad. So that’s helpful too.

Arvid Viaene: I think one of the points in your paper is that CBAM revenue is a lot lower than you might expect, because companies internationally reshuffle: cleaner production gets sent to Europe and dirtier products get sold abroad. That reallocation makes projected CBAM revenues lower.

Kim Clausing: Yeah—from the CBAM. The carbon price is still bringing in a lot of revenue. Countries might think about their fiscal needs as they contemplate these policies. Can they come up with any idea that’s more efficient than a carbon price? Most other taxes create inefficiency, whereas a carbon price helps efficiency by reducing the negative effects of the externality. Most economists love carbon prices for a reason.

Arvid Viaene: It’s true. I’m a big fan of it. Anytime this topic comes up, I’m very positive about it. One of the main results is producer surplus falls by 23 billion, but then it changes after CBAM where there’s an improvement—while consumers lose. Could you talk about those trade-offs?

Kim Clausing: Yes—and I should emphasize that quantitatively it’s not a huge effect, but it’s in the direction we would expect. For producers, because the CBAM offsets the disadvantage of serving their own market, they recoup some of the lost market share they would have had if the carbon price occurred absent the CBAM.

That’s a benefit to them, but consumers are on the other side of that in a nearly symmetrical way. The dollars producers recoup, consumers lose as they don’t get cheaper, dirtier imports.

But when you look at the magnitude of consumer loss here, it shouldn’t be standing in the way of policy adoption. It’s incredibly small as a share of these markets—and if you think about a consumer’s bundle: if you’re losing $2 billion in consumer surplus in all of Europe from the aluminum market, it’s an indiscernible tiny share of people’s consumption.

Kim Clausing: The consumer side of this shouldn’t be stopping policy. The key is to find a policy that producers can stomach enough that government can get it through, and that’s where the CBAM helps.

Arvid Viaene: Exactly. Also because producers are more concentrated—easier for them to coordinate.

Spillovers abroad: who wins and loses outside Europe

Arvid Viaene: People say poor-income countries or other countries might be impacted by CBAM, but what they forget is that prices in Europe will go up, while prices abroad might decrease—so it might actually be good for consumers abroad. Could you talk about that mechanism? You did calculations for India, too. The narrative is usually driven by producers abroad being vocal about it.

Kim Clausing: There are diverse effects. Consumers in unregulated markets benefit from the increase in supply. We have a table in the paper. One of the big winners is U.S. consumers. We have a large market and we’re importing a lot of these metals. When the price falls in unregulated markets, that helps consumers.

There are consumers that lose in the regulated market, and producers that win and lose. The winners tend to be firms in the clean-energy space: they get the benefits of a higher-price market without fully offsetting that benefit with additional carbon fees through purchasing permits in the ETS.

Beneficiaries tend to be firms with very clean production, and losers are firms with dirtier production. If administered at the plant level, it’s possible that within one country you’d have both winners and losers. We also talk later about trade-offs between administering at the plant level versus the country level.

How big are consumer price effects?

Arvid Viaene: You said the consumer losses in Europe aren’t big—around 2 billion. Was that surprising to you? What reactions have you gotten?

Kim Clausing: I was a little surprised, because you hear a lot of anxiety around higher energy prices. That’s understandable for Europeans who faced price shocks around Russia’s invasion of Ukraine and what that did to utility bills and heating costs.

So people are anxious about energy prices writ large. But in these heavy industries—which are a substantial share of worldwide emissions—these price effects are really quite small for the typical consumer bundle.

I don’t think it makes sense to base climate policy on fear. Just because people are worried about utility bills to say, “Oh, we can’t raise the cost of a toaster by one dollar if it might have metal in it,” or one cent—that’s not going to be very much.

People should have perspective and some understanding of the magnitudes. And it’s not going to be that salient. If these basic goods’ prices increase, you’re not going to see that at the cash register, because these are input goods into complicated production processes with lots of other costs. So it’s not going to have a noticeable impact on end consumers.

Emissions reductions and leakage under CBAM

Arvid Viaene: Another part of your paper is the goal to prevent emission leakage. Could you talk about the emission leakage results?

Kim Clausing: Yes. Emissions go down substantially from the carbon pricing itself. Even at a semi-conservative social cost of carbon, you can see that global welfare—if you included the benefits from reduced emissions—improves with this policy. In the working paper version, we show global welfare on the private side without including the negative effects of the externality.

But the emissions reductions are substantial and would move the policy into a welfare-enhancing regime at most social costs of carbon. Emissions reductions are larger with the CBAM than without. It’s not an enormous difference because there are confounding effects, but you get more emissions reductions—maybe on the order of 5% or 10% more with the CBAM than without.

That’s particularly true when it’s just Europe as the regulator, which is the policy experiment we’re looking at right now. If you add China in, things get more complicated, and that’s worth looking at too because China is such an important producer in these heavy industry goods.

China’s role and the climate club logic

Kim Clausing: China is a dominant producer—really 50 to 60% of these metals. Ideally, China would join a coalition that priced carbon at reasonable levels and levied a carbon border adjustment mechanism too. In that instance, you don’t see as big of an impact with the CBAM. In a way, the CBAM isn’t doing the work because you already have the lion’s share of world production carbon pricing.

Then the CBAM becomes more of an incidental tool—effective in expanding incentives to carbon price in the first place. We show that when a country decides whether to carbon price, they see it’s better for them if they also include a CBAM. That should tilt people toward joining those regimes.

Arvid Viaene: When you say “better,” it becomes less costly because Europe has already imposed this cost. It’s still costly for China, but relatively less costly once the CBAM is in place.

Kim Clausing: Yes. And China should consider doing a CBAM when they implement, because that will also make their policy more welfare-enhancing for China.

Arvid Viaene: Exactly. China being 50 to 60% of emissions in these industries is huge. It’s almost the Nordhaus climate club vision.

Kim Clausing: I don’t think it’s a ridiculous dream. They’re a huge part of emissions in these industries. Overall their footprint isn’t 50 to 60%, but they’re very important in heavy industries. They’ve shown willingness to do carbon pricing in these industries. Recent Chinese policy expanded their emissions trading system to include these heavy industries, which is thoughtful.

Right now the prices are quite low, so they’re far from Europe price-wise, but the approach is similar. That’s promising for a Nordhaus-type climate coalition. And at the recent COP—there was announced more coordination on carbon pricing toward moving in that direction, and that could be helpful.

Arvid Viaene: Exactly. That’s encouraging. I recently talked to a policy expert on CBAM, and one of the things you get because of CBAM is companies abroad start to measure everything—get the measurement problem right. People forget how measurement-intensive this is. Even the EU ETS took a long time to set up mechanisms to monitor and ensure it’s right.

Investment response: how CBAM can encourage cleaner production

Arvid Viaene: You have an interesting simulation of how CBAM could encourage green investment. Could you talk about what you did there and what the idea is?

Kim Clausing: The idea is to allow emissions intensity to respond to carbon taxation. We take, as given, a semi-elasticity, which one can vary. Then we simulate market expansion over time.

You could imagine that over time the world is growing and demand is growing. If you allow new capacity in these sectors to respond by adopting mitigation steps that lower emissions intensity, you find that the policy amplifies emissions reductions and lowers abatement costs, because firms can respond by adopting cleaner processes.

One tricky thing in the short run is we have the smelters and plants that we do. They can expand supply a bit, but we’re not looking as carefully at what the next plants look like. Letting emissions intensity respond is a nice feature of that exercise and provides encouraging results: larger emissions reductions and lower abatement costs.

Arvid Viaene: Exactly. Reading the paper, it’s easy to get lost in technical details, but this was like: this has a lot of really good impacts.

Kim Clausing: Yeah.

Her number 1 take-away from the paper

Arvid Viaene: What’s the number one thing you want listeners to take away from the paper?

Kim Clausing: One of the hard things about global collective action is the incentive problem. With climate change, it’s tricky because there are free rider effects between ambitious jurisdictions and less ambitious jurisdictions.

There are also competitiveness effects: if you impose costs on your industry, you’re hurting them relative to industries in other countries in this global marketplace. The big lesson is that this is an important new tool. We model key implications of the tool. But one thing we don’t get to is the importance of this in political economy stance.

What the paper can show you is what happens when we adopt CBAM, and it’s a pretty nice story—it’s straightforward, it’s what you would expect. Where it gets really exciting is thinking about what happens at future COPs and what pushes countries to solve the global collective action problem.

You need an answer to jurisdictional spillover questions. CBAM has a big impact in political economy: it makes it easier to carbon price domestically because you have an answer to domestic industry on competitiveness.

It also makes it easier to encourage more countries to come into the fold and do carbon pricing as governments see they can convert tariff revenue that would have accrued to regulating countries into domestic revenue—which every country needs for its fiscal situation. That’s the biggest takeaway.

Arvid Viaene: Thanks. When you say it, I can see the process over many COPs where China raises it a little bit, that makes it more costly for others who then raise it a little bit. You get an iterative process of inching upward to more global cooperation on carbon.

Kim Clausing: Right.

What surprised her the most most while writing the paper

Arvid Viaene: Was there something that surprised you during the writing of the paper that you hadn’t anticipated?

Kim Clausing: Two things surprised me. One was this flat emissions gradient. People make assumptions about emissions intensity that don’t fully reflect reality.

One example: aluminum is incredibly electricity-intensive. If you’re making aluminum where you can rely on hydropower—and many poor countries have hydropower, Mozambique is one example—you can make aluminum with a much smaller carbon footprint than people might think.

So there isn’t this sense that richer countries, in a per-capita income sense, have lower emissions intensity at the plant level in these industries. That’s encouraging for the policy.

A second thing that surprised me is the small quantitative effects here. We’re talking about something that could affect—if you take all the CBAM industries—maybe as much as a fifth of global emissions.

And we’re letting tiny welfare losses, and tiny consumer and producer losses, stand in the way of progress.A meta message is: there aren’t many negatives associated with doing the right thing here. You’re not going to have trouble offsetting these kinds of costs with other policies. The tax policy toolkit is filled with tools where you could offset negatives and still achieve massive emissions reductions.

So the small size of consumer and producer surplus losses—and welfare losses—is indirectly encouraging, even if it’s hard to wave in front of referees: “Oh, look, small numbers.” In this context, small numbers can be a good thing.

Arvid Viaene: Thanks so much. I think that was great. We can end it there. Your paper really helps put numbers on the debate and not just get stuck. I was one of the people who had this idea of varying carbon emissions intensity in my mind. Thanks for the paper, and for joining.

Kim Clausing: Happy to help. Our revision of this paper to satisfy various journals will include other industries in the stylized facts. It tends to hold up. For electricity, you see a flat gradient, and for fertilizer as well. We haven’t looked at cement, but cement is non-traded anyway. People aren’t lugging cement across borders very often.

Arvid Viaene: Awesome. Thank you so much, Kim.

Kim Clausing: All right. Take care.

Now, in my view, one of the main criticisms is a credibility concern. And it is a legitimate one, because in the past there have been major credibility issues with offsets. For example, in episode four of this podcast, I interviewed Ben Probst, an ETH Zurich professor, who co-authored a paper finding that for a sample of one billion credits under the Kyoto Protocol, only one out of five credits actually reduced CO2.

And as we saw in episode 11 with Jos Delbeke, the supply of cheap, sometimes fraudulent credits drastically reduced prices in the EU’s emissions trading scheme. So as a result, the EU cut them out in 2013. However, the EU has now put carbon offsets back on the table. But here is the key element. The EU deal specified that those carbon offsets have to be generated under Article 6 of the Paris Agreement. And the Paris Agreement Article 6 is the world’s attempt to create better rules, but I know very little about it.

So in this episode, we’ll discuss what Article 6 of the Paris Agreement is, what it covers, and whether it can avoid some mistakes of the past. And to do so, I’m delighted to be joined by Beatriz Granziera, an expert on this topic. Beatriz is a senior policy advisor at the Nature Conservancy, where she leads TNC’s global strategy on international carbon credits and large scale forest programs.

She brings extensive experience on the Paris Agreement Article 6 negotiations and its links with nature and other carbon markets. and has been supporting developing countries in translating Article 6 rules into domestic policy. And Beatriz has authored several publications, including an Article 6 explainer, which I read and I really recommend it, an Article 6 implementation article, REDD+, and Article 6 explainers, contributing to the global understanding and application of complex climate themes.

She holds a Master’s in Environmental Policy from Yale University and a Master’s in Environmental Law from the Catholic University of São Paulo. So welcome to the podcast.

Beatriz Granziera: It’s a pleasure to be here. Thanks.

What is Article 6?

Arvid Viaene: As I said, I think Article 6 is now on people’s radar, but it’s a very unknown quantity. Just to get us started, would you mind explaining kind of what Article 6 is?

Beatriz Granziera: Yes, absolutely. And I think just that question tends to get very tricky, very fast. So, Article 6 of the Paris Agreement is a framework that allows countries to work together to meet their mitigation targets more cheaply and effectively.

And with that, hopefully, to raise ambition. There are three ways in which countries can do that. So I’m going to very briefly just talk about them. Two of them are market-based and one is a non-market approach.

So the first market approach is called Article 6.2. This is not a great name, but this is just how it’s known. Article 6.2 sets rules for countries to cooperate directly—typically through a bilateral agreement. It’s a direct relationship between countries—through a bilateral agreement, for example, or even between a country and a company. And because it’s a direct relationship, there’s a lot of flexibility from the buyer and the seller to decide what they want to trade and how they want to trade.

The second mechanism, it’s called Article 6.4 or the Paris Agreement crediting mechanism. And that’s different. So this is a centralized system overseen by the United Nations. And it’s very similar to what we had in the past in the Kyoto Protocol with the Clean Development Mechanism. Because the UN centralizes this mechanism, it decides what methodologies are eligible, what sectors are in, what sectors are out and what rules apply.

And then third, you have the only non-market approach under Article 6, which is called Article 6.8. And it’s basically around climate finance. So the main point here is that there are no expectations of trading of carbon credits. And this mechanism is way, way less developed than the market track. So I’m not really going to focus on that here.

But before we move on and before we get into the individual components of Article 6, I think it’s important to take just a quick step back to understand what Article 6 means in a broader landscape of carbon markets. Because today you have several different markets that work in parallel. So you have the voluntary carbon markets where companies can purchase carbon credits to meet their voluntary climate targets. You have a lot of domestic compliance markets. You have some international markets such as the aviation market or CORSIA, you have Article 6. And what’s very interesting about this moment that we are living right now is that the lines between these markets are blurring more and more. So they are continuing to function in parallel, but more and more one market is influencing the other and they don’t work in isolation anymore. So to that question, what is Article 6? And when we talk about this, I think we can no longer assume that Article 6 is just another technical rulebook under the UN because now Article 6 is really a mechanism that sits at the center of the super complex landscape of carbon markets. And it’s already influencing how these other markets are evolving.

Arvid Viaene: So thank you. So if I were to summarize it, it’s you’ve got several of these markets, you’ve got the voluntary carbon market, you’ve got the aviation one, and now Article 6 is like the new player in town. And it’s already starting to shape the other ones. And then in Article 6, we’ve got Article 6.2, which is kind of buy, a It’s kind of a relationship between two parties. And so it’s kind of or like companies, countries, and it’s more flexible. And then you’ve got Article 6.4, which is the centralized system. So UN rules apply and govern the carbon offsets.

Beatriz Granziera: Yes, exactly. I think you nailed it. So one is very flexible. of course, you still have to follow some rules like, and sorry, So yeah, exactly. one is way more flexible and allows countries and the buyer and the seller to have a lot more flexibility to decide again what they’re going to trade.

And Article 6.4, because you have that centralized UN body, which is called supervisory body, then it’s basically you have to follow the rules that this body sets. So I think just some countries might want to move faster and want have more flexibility, might choose to go with Article 6.2. Other countries want that standardized credit with a UN stamp, that hopefully get where guarantees quality. So they might go with Article 6.4.

How Paris differs from Kyoto

Arvid Viaene: And that leads me to the next question is that think the prior interview Ben Probst, he was looking at carbon offsets under the Kyoto Protocol. Now we’ve got the Paris Agreement., what has changed in this Paris Agreement versus the Kyoto Protocol with the clean development mechanism?

Beatriz Granziera: There are a few very big shifts there since Kyoto. So first, right, Kyoto was just one centralized system, the Clean Development Mechanism, very similar to what I just mentioned around Article 6.4. At the time, we also had this centralized UN body controlling everything related to the operationalization of the Clean Development Mechanism. But under the Paris Agreement, as I mentioned, countries have a lot more flexibility to decide how to engage in markets, for example, through just signing a bilateral deal under Article 6.2.

Second, and I think this is a really key difference here, that under the Kyoto Protocol, only developed countries had binding targets for climate. That means that developing countries could then sell carbon credits without that really affecting their national accounting. So as a result, double counting was not really a concern back then. But this is different now under the Paris Agreement because every country has a mitigation target or an NDC, and that basically changes everything. So If a country sells a carbon credit today, it has to adjust its own emission balance to make sure that the same emission reduction is not counted in another country at the same time. Because if you’re counting one emission reduction twice, that won’t help as the goals of the Paris Agreement. And then that has some major implications that we get can get more into later. But now developing countries have to really think what kind of credits they are selling and what quantities and at what price.

And just, I’ll say that the third big difference here, a little bit related to what I’ve already mentioned, is that the landscape of carbon markets today is way more complex than what we had under Kyoto.

Now you have more than a decade of experience with voluntary carbon markets and a lot of lessons learned from what worked and what really did not work. You have large scale forest programs generating credits for the first time. and on top of that, there are today over 70 regulated carbon pricing systems around the world, including carbon taxes and emission trading systems. So with countries, for example, like Brazil now entering the space. So Article 6 is both shaped by and shaping all of these markets as well. And the rules are also hopefully learning from all this experience that happened in the past couple of decades.

Arvid Viaene: Thank you. And I think it’s also worthwhile pointing out that this is something I learned that I wasn’t aware of is that exactly under the Kyoto Protocol, there were no targets for some of these countries. So they could sell credits without it impacting their goals. But now that has changed with the Paris Agreement. So the double counting topic that you can only use it once becomes really important. And I was even kind of surprised that this used to be the case. You could just buy credits that the other person then didn’t need to account for. So, yeah, first when I read that, I’m like, huh? But it makes sense that is now a goal. So, and then this double counting is, as I understand it, addressed in Article 6.4, which is kind of the centralized system, if I can call it that.

Arvid Viaene: Is that also there in Article 6.2 in this bilateral system?

Beatriz Granziera: Yes, it is. Article 6.4 and Article 6.2 both need tools in place to avoid double counting. This may sound simple and obvious, but it was one of the main sticking points in the negotiations for years. Article 6 is one of the many articles of the Paris Agreement, and it took countries almost a decade to finalize rules. Almost all other articles were largely agreed in 2018 in COP 24, but Article 6 is really complex and that issue around how you really address the double counting was at the core of very heated debates throughout all these years.

Arvid Viaene: Why was it so heated?

Beatriz Granziera: Because we were coming from the Kyoto Protocol. So developing countries, a lot of them still had some expectations that they could still sell credits without really that affecting their own climate commitments under the Paris Agreement. So, and I think there is, Kyoto was divided between developing countries and developed countries. So it took a lot of time for countries to transition to this new Paris universe.

And I think addressing the double counting for all countries is a key point of Article 6 and really the core of why this system can work. Because unless you have, all countries moving towards reducing emissions, the system just, it doesn’t make sense in this new reality that we have right now.

Arvid Viaene: Exactly. So, and I can also, imagining that the EU exactly has this as a big condition that you want to have this double counting or otherwise it won’t reduce global emissions. So...

How big is the Article 6 market today?

Beatriz Granziera: Yes, exactly.

Arvid Viaene: Just to get like a sense of what the market is before we dive into the further technicalities, could you just give us an idea of the size of these carbon offsets, like how have been generated over the past or the past five years? And I know might get complicated with like those issued under Kyoto and now, but just kind of getting a sense of the landscape.

Beatriz Granziera: Now, I think that’s actually a really important question because there’s a lot of buzz around Article 6 right now. But when you look at the actual market and what’s happening, you realize very fast that we’re just at the very, very beginning. Just to break it down, you have around Article 6.2, So the bilateral agreements, you actually have a lot of momentum. There are over 80 bilateral agreements that have been signed between countries to date. But then when you look at the actual trades between countries, the number falls to two. So only two trades have happened. One was between Switzerland and Thailand back in 2024. And the second one happened a few months ago between Switzerland and Ghana.

So this is a market that hasn’t really even started yet. So there are a lot of reasons why that’s the case. So first of all, after a decade or almost a decade of negotiations, a lot of countries are still regulating Article 6 domestically. And that’s complicated. That requires sometimes congressional approvals, different legislations, different, negotiations. So that just takes time. The second [reason] is that there’s a lot of uncertainty now about how countries will get to their climate targets. Just to explain, climate targets under Paris Agreement, they are updated every five years. And then the next target to 2030, it’s coming up, but countries are not absolutely sure yet where they’re going to be there. So they have to be careful about how many credits they want to sell under Article 6, because these credits will not be able to use for them to meet this climate target. So this is a very big component. And the third thing is that demand for Article 6 credits is still small and quite fragmented. So overall, Article 6 is up and running, but it hasn’t really turned into a liquid market yet. So to your question, like how many credits we’re talking in terms of supply, we don’t know yet.

And there are very few countries that have, the legal framework in place, the institutions in place and a pipeline of carbon credits that could qualify for Article 6.

Arvid Viaene: Thank you. And then I think that does stand in contrast to the voluntary carbon market, where I think one of the big things that I’m learning is this course, yeah, like the aviation is like a big source of demand for credits.

Could you maybe speak a little bit more to that? Because even in your projected demand for 2030, they were in there.

Beatriz Granziera: Yes, absolutely. So I was talking before about supply of Article 6 credits and how that is slowing happening. But then another huge component of any market is where the demand is coming from, right? Who is going to buy in the end Article 6 credits? So today, as I mentioned, Article 6 demand is not there yet. It’s fairly small, but it’s slowly emerging. So demand for Article 6 comes basically from two sides. One, you have buyer countries, mostly developed countries like Switzerland, Singapore, Sweden, South Korea, Norway and Japan. They want to use Article 6 credits to meet their own climate targets.

So these countries have announced some demand, and this is by 2030 200 million tons of CO2. But as you very correctly mentioned, the bulk of Article 6 demand comes from CORSIA, which is the aviation sector where companies would be purchasing credits to meet their own goals under this Corsia market. But I think there’s one thing that is important to mention here, that this is just, the numbers that I mentioned are just a photo of what we have today, and they will for sure change in the future. So as we get closer to 2030 and also closer to 2040, more and more countries might rely on Article 6 to meet their own climate targets.

And I think one of the biggest examples that we have is the European Union that announced just in December of last year, 2040 target, which allows of 5% of Article 6 credits. So that 5% might not sound a big number, but it’s actually a huge game changer for Article 6 demand. And just the EU alone could double all the current Article 6 demand that we have today to 2030. So that’s definitely going to be a big deal in how the market progresses.

Arvid Viaene: Could we talk about the EU demand just for a second? Because one of the things I was surprised by when I read your article is the timeline of the EU demand. So could you maybe talk about how they’re thinking of implementing this?

EU 2040 target and the return of international credits

Beatriz Granziera: Yes, absolutely. So, as I mentioned just last month, the EU finally agreed on their 2040 targets, and that’s a 90% reduction in emissions compared to 1990 levels. The big novelty here, as you mentioned in your introduction, is that for the first time in many years, the EU will allow 5% of this target to come from the use of international credits, and that’s basically Article 6 credits.

Arvid Viaene: Article 6.4, right?.

Beatriz Granziera: Article 6 in general,

Arvid Viaene: Got it

Beatriz Granziera: Yes, the EU, from what the EU has been announcing, it’s not yet clear. And I can talk a little bit more about the uncertainties that we have coming up in 2026 and the following years. But just in terms of timing, the use of international credits would be available from 2036 onward. And before that, you’d have a pilot phase running from 2031 to 2035. There’s not a lot of clarity on how the pilot phase is going to work. But that’s that’s just how the EU is structured. That’s the target.

And again, I think I want to emphasize this many times because, when you hear 5%, that might sound small, but politically it’s actually a big shift for the EU. Because for a long, long time, the EU has been very clear that it wanted to meet its its climate targets only with domestic mitigation inside the EU. So this decision to reopen the door to international creditS has definitely made the waves here in Brussels and well beyond.

Beatriz Granziera: And I can talk a little bit about the different positions here.

Arvid Viaene: Yeah. and Did it surprise you? Had you seen something coming?

Beatriz Granziera: Actually, it did surprise me when it first came. So these discussions, the first announcement came in July of this year. And we are used to see the EU in the Article 6 negotiating rooms, very clear that they won’t use these credits for, maybe, a decade of negotiation. So that was that was actually a surprise. But at the same time, the EU has been one of the main negotiators and decision makers in this process. The EU has been around the negotiation since the Kyoto Protocol. So on the other side, it makes sense that you might want to use, that is one of the flexibility mechanisms.

Arvid Viaene: Maybe we then, know, because they announced that some people were surprised and some people were against the use saying, we should keep all reductions domestic. I think there’s a case to be made to use credits from just a theoretical point. If you want, can reduce them somewhere cheaper. But there are then, of course, some worries. And I think one of the worries we talked about with Ben in his episode is what I would call flooding of past low quality credits.

Because under the Kyoto Protocol, you had these credits that sometimes were of lower quality or sometimes might have not mitigated CO2 or might have not reduced CO2. and now there’s this whole discussion as I get it about how do we transition those prior credits, if at all. So maybe could you talk about what the transition mechanism could you talk about what the transition mechanism is. Because I imagine those are also intense discussions.

Can old Kyoto credits flood the market?

Beatriz Granziera: Yes, absolutely. And you’re right. That has also been another important seeking point. So I think your question has two points there. one the criticism about the EU being open to the use of Article 6 credits in general. And the other thing, how this old Kyoto Protocol credits, and a lot of them, don’t have the same quality standards, would get into this mechanism. So I’ll just break it down and start talking about the criticism that we have been hearing here in process.

So I think one of the major concerns is whether relying on international credits would weaken climate ambition inside the EU or even risk increasing emissions domestically. Right. And I think that’s a very valid concern and definitely deserves serious attention, but I think this is only part of the picture because using Article 6 isn’t automatically good or bad, and it doesn’t decrease or increase ambition. What really matters it’s like are the details, right? And many of these details haven’t haven’t been decided yet. And this is what the Commission is going to start doing this year now.

So big questions that are still unanswered are: which sectors are going to be allowed, which methodologies? Is the EU going to use Article 6.2 Article 6.4 only? What safeguards will be in place? How will member states participate in the decision of how to purchase these credits.And, I think very importantly, what kind of buffers and quality controls will ensure that the credits coming in the EU are actually high quality and real and additional and verified.

And I think there’s also another point that I feel that is often overlooked in this discussion as well. By entering this market, EU is not only benefiting from the credit credits, but because the EU represents such a huge demand, it will also shape how the supply of credits will develop.

And right now, I mentioned before, we’re just at the beginning of the market. So supply has not yet been locked in. So the fact that EU is entering the market represents a big opportunity for Europe to shape how developing countries are developing the credits at what quality criteria with what ambition. And I think this is a very rare and timely opportunity that the EU have in the end, the EU participation could really drive more global ambition of this market, depending on how it’s done.

Arvid Viaene: Yeah. And in some sense, it’s because they then represent such a big potential demand, they can also have potentially more influence on the rules that go into it.

Beatriz Granziera: Yes, absolutely. Because, developing countries are looking at demand. So if there’s a clear demand signal to use, certain standards and, to have certain ambition, that’s how, where the market’s going to evolve. And the EU is one of the very few players in the market that has, the size and and scale to really shape all of this.

So I think this is, and this is like the side that I don’t feel it’s being talked about in Brussels that much, that the EU could have a huge influence on the quality of carbon credits that could then be developed in the future.

Arvid Viaene: And then we have the transition of the old credits.

Beatriz Granziera: Yes. So you’re right. The Clean Development Mechanism, some Clean Development Mechanism credits could transition to Article 6.4, but that’s there is one catch there. For most product projects, the deadline has already passed. So it was established in 2021 that like old projects from the Clean Development Mechanism could request transition until 2023, with the exception of afforestation and afforestation projects, which extended the deadline until 2025.

But then even when the project developer requests the transition, it’s up to the host country to decide if they will allow the transition. So this is a very important point. And this is one thing that was very discussed at COP30 in Bellin just a few months ago or couple months ago. That deadline for countries to approve the transition was extended by six months until June 2026. Without that approval, the transition won’t happen.

So if you look just in terms of how many projects requested transition, you have around 1,400 projects that could lead to, in the higher end, maybe a billion credits entering transition. maybe flooding at the Article 6 market. But in reality, the number of projects and credits that we transition will transition will be much lower because you require that host country approval.

Arvid Viaene: I think I read somewhere it’s like of the billion around 300 million would be allowed to enter or do I get that wrong?

Beatriz Granziera: Yes, I think that there are some estimates. I think the World Bank has come up with estimates around that number. But for me, when I talk to countries that are going through the very bureaucratic process of approving, the projects and people that have on their desks just a pile of projects that they are deciding to approve, I feel that this is still quite uncertain. Because a lot of countries, they still don’t know if they want to approve the projects for the reasons that I mentioned before.

If they approve the transition with a corresponding adjustment, that means that they cannot use these credits to meet their climate targets. So countries are being very careful. And I think it’s very hard to estimate how many credits are going to enter the market. The other important issue here is that it’s a market, right? So even if some credits from the CDM are allowed to transition, it’s up to the buyers to decide to buy them.

So if the EU, as you mentioned, like that concern that the EU would then be, buying CDM credits, that’s up to the EU. The EU can decide what kind of credits they will buy. And I think there is a big concern around quality on the CDM project. So I’m very curious to see how the market reacts to them and how much demand for these credits are and what price.

Quality control under Article 6.4

Arvid Viaene: So maybe that’s a good point to transition to Article 6.4 and the quality control on credits. Because as the way I read your explainer, it seems like there’s a lot of stringent quality control going on with the supervisory board. Could you talk more about what that supervisory board is doing and what the status is?

Beatriz Granziera: Yes, absolutely. And I think 2025 was a big year for Article 6.4 and the supervisory body. And everyone there worked really, really hard, including the UNFCCC Secretariat. So we had some very big milestones. For example, the first ever methodology eligible under Article 6.4 was approved just back in October for landfill methane. The first projects also started to transition.

Arvid Viaene: Just when you say it’s been approved for landfill methane, that means that every project in landfill methane meets all these requirements, it can officially enter in Article 6.4. There’s no more need for approval or like you would need some verification. Just what does that actually mean that now it’s been approved?

Beatriz Granziera: Oh, there’s a lot of approval. let me clarify: I think 2025 was a very big year for the Paris Agreement crediting mechanism or Article 6.4, with some very important milestones that the supervisory body and the UNFCCC secretariat achieved. Just to mention some of them, there were, for example, some very important rules that were draft. These are overarching rules around technical issues on permanence and additionality, leakage, baselines and all of that. Very important and very technical issues on how the market will work.

On top of the super broad and overarching rules, now they are also working to approve specific methodologies. So methodologies are basic, like, activity tailored rules that every project would have to apply to be eligible for Article 6.4. This will take time. The first methodology has been approved already. It was approved in October of 2025. And it’s just for landfill methane.

But now for 2026, the supervisory body will likely consider a lot more methodologies. So more projects and more types of activities can also be considered under Article 6.4. And then the other milestone is that projects already started to transition. So far, we don’t have any new project because we didn’t have methodologies until October, but we have some of those CDM-old projects that were that transitioned to Article 6.4. So definitely some very big moments for Article 6 right now.

And I think in terms of quality, this is a very key component because most of when you look at who is making these decisions, a lot of them were around making the same decisions under the CDM. So they, they [experienced the difficulties of the CDM quality control]. In fact, in many aspects, the quality issue was a big problem there. So you see that like quality control is a really big focus, as it should be. I think in general, it was a deliberate decision that one way to control quality is that to make very stringent rules. And with that, of course, you’re going to reduce the supply of credits that would be available to be generated.

So I think this is where we are right now. But I think there are other points to be considered in these discussions as well that were very, very evident and very important in 2025, because what you’re actually developing is a market, right? And a market needs to be feasible and needs to work if you want to deliver the goals of the Paris Agreement.

So if you implement rules that are really good on paper, but just they don’t work in practice, the system just won’t deliver mitigation and scale to meet the goals of the Paris Agreement. So I feel that right now you have that this tension between two sides. One side pushing to make rules very, very stringent and as they should be. But also some questions around to what point you pushed too much in a sense that you actually don’t deliver any of the goals that you are intended to deliver within a carbon market mechanism.

Arvid Viaene: So it’s like the balance between too stringent, it won’t generate any credits and then to lose you, you get a big concern about the quality. But right now, it sounds like if the rules get too stringent, there might just not be any, not, if the rules get too stringent, there might not be any credits. If, that’s a summary.

Beatriz Granziera: Just to give you an example, I think one of the biggest discussions of last year was around the role of nature-based credits within this market and how that would work. So, I think starting in the summer until the very end of last year, that was one of the biggest and most heated topics that I think it really went from, the super technical like policy nerd discussion to become a very big political issue. We had, Forbes, Reuters covering this issue. So it really became important. But basically, the supervisory body was drafting rules around permanence and the risk of reversals. And hundreds and hundreds of stakeholders in many countries raised concerns that these roles were so stringent that they would basically exclude nature from Article 6.4 altogether. And, as I was mentioning, this is not only about Article 6.4, because now all these markets are interconnected.

So this would really mean that nature would be affected in other markets as well, such as the voluntary carbon markets and other compliance markets. So I think this is an example of how, rules that might sound good on paper, in the end, could exclude one of the most important sources of supply. And nature is not only about reducing emissions, you have very important co-benefits for communities, for water, for so many other things. So, again , I think there are concerns around quality are important and they needed to be addressed. But I think risks should be addressed with risk management mechanisms, not only simply excluding full sectors from the market.

Arvid Viaene: It sounds like the rules might even get too stringent.

Beatriz Granziera: What I think is that the supervisory body developed some very important rules that are looking at quality controls. And as I mentioned many times, you cannot have a market if you don’t have very stringent quality control. So this is for sure important and this is what is wanted. But to your question on whether the supervisory body went too far, I think we don’t know yet because there are still a lot of rules that are going to be discussed in 2026, some very important components as well.

And I think to answer your question, we’re really going to have to wait until the methodologies are approved. So, as I mentioned, you have overarching rules, but like these discussions will come back over and over again when you when you approve methodologies.

All methodologies need to be approved by the supervisory body and all projects also need to be approved by the supervisory body. So these discussions will come back over and over again. And I think only then we will have a real sense of, how the market’s going to work.

Arvid Viaene: So, It sounds like the Article 6 is really like taking off like 6.4, the landfill methane was approved. Next year, we’re going to look at other projects. I think that’s my sense and takeaway is that this is all starting. This is all happening right now. Like it took a long time until COP29 to kind of agree on the things. And now it’s like starting to kick off for Article 6.4.

Beatriz Granziera: Yes, exactly. For Article 6.4, it has been a very slow development. So Article 6.4 is just now becoming operational for the first time. So, you haven’t had any trades yet. And this is, I think we only see how the market evolves when you actually have the trades. We will only see how stringent or how, feasible the market is when you actually start to have trades.

So I think I agree with you. This is a very exciting time to see how things evolve for, again, for a market that has the potential to be, a very big deal within the landscape of carbon markets and that is already influencing, how other markets consider high quality.

Arvid Viaene: Perfect, thank you for coming on. I think this is going to really help people get a sense of Article 6 instead of the abstract to actually get to know it. So thank you so much.

Beatriz Granziera: Awesome. That works. Great. Thanks, Arvid. It was really a pleasure to meet you and thanks So much for the invitation. It was great to participate here.

Introduction

International carbon credits are back in the policy conversation—especially after the EU’s new 2040 proposal reopened the question of whether (and how) Paris Agreement Article 6 credits might play a role.

But “offsets” are a loaded term for a reason: past systems created large volumes of credits, and a recurring critique is that too many didn’t represent real, additional emissions cuts.

So what is Article 6, what’s genuinely different under Paris, and what still isn’t settled?

In Episode #18, I’m joined by Beatriz Granziera (Senior Policy Advisor at The Nature Conservancy), who works on Article 6 negotiations and implementation, including supporting developing countries on domestic Article 6 policy.

We cover:

· What Article 6 is trying to do—and the difference between 6.2 (bilateral/decentralized) and 6.4 (UN-governed centralized mechanism)

· Why Paris differs from Kyoto: every country has an NDC, so accounting rules matter—and how corresponding adjustments aim to prevent double counting

· A market reality check: many agreements, but very little actual trading so far—and why countries may be cautious about selling reductions they might need for their own targets

· The EU angle: why EU demand could reshape standards (and why details matter more than slogans)

· Transitioning old Kyoto/CDM projects into Article 6.4: what “flooding” risks look like in practice and why host-country approval becomes pivotal

· The core tension ahead: quality vs scale—rules can be strong on paper, but too stringent rules can leave a mechanism that can’t generate meaningful supply

Related episodes:

· #4 Dr. Ben Probst — Can We Trust Carbon Offsets? Evidence from 1 Billion Credits

· #11 Dr. Jos Delbeke — The History of the EU ETS: Key Turning Points, Challenges and Policy Lessons

Start Transcript

Arvid Viaene: Hi, and welcome to another episode of the Climate Economics Podcast. And recently, the European Union set new 2040 climate targets. And a novel twist is that the 90% reduction target allows international carbon offset credits to be used for 5% of those reductions. And carbon offsets are a mechanism where a country or company can buy CO2 reductions from another country or company. Now, this decision by the EU has sparked a big reaction and pushback for a variety of reasons.

Now, in my view, one of the main criticisms is a credibility concern. And it is a legitimate one, because in the past there have been major credibility issues with offsets. For example, in episode four of this podcast, I interviewed Ben Probst, an ETH Zurich professor, who co-authored a paper finding that for a sample of one billion credits under the Kyoto Protocol, only one out of five credits actually reduced CO2.

And as we saw in episode 11 with Jos Delbeke, the supply of cheap, sometimes fraudulent credits drastically reduced prices in the EU’s emissions trading scheme. So as a result, the EU cut them out in 2013. However, the EU has now put carbon offsets back on the table. But here is the key element. The EU deal specified that those carbon offsets have to be generated under Article 6 of the Paris Agreement. And the Paris Agreement Article 6 is the world’s attempt to create better rules, but I know very little about it.

So in this episode, we’ll discuss what Article 6 of the Paris Agreement is, what it covers, and whether it can avoid some mistakes of the past. And to do so, I’m delighted to be joined by Beatriz Granziera, an expert on this topic. Beatriz is a senior policy advisor at the Nature Conservancy, where she leads TNC’s global strategy on international carbon credits and large scale forest programs.

She brings extensive experience on the Paris Agreement Article 6 negotiations and its links with nature and other carbon markets. and has been supporting developing countries in translating Article 6 rules into domestic policy. And Beatriz has authored several publications, including an Article 6 explainer, which I read and I really recommend it, an Article 6 implementation article, REDD+, and Article 6 explainers, contributing to the global understanding and application of complex climate themes.

She holds a Master’s in Environmental Policy from Yale University and a Master’s in Environmental Law from the Catholic University of São Paulo. So welcome to the podcast.

Beatriz Granziera: It’s a pleasure to be here. Thanks.

What is Article 6?

Arvid Viaene: As I said, I think Article 6 is now on people’s radar, but it’s a very unknown quantity. Just to get us started, would you mind explaining kind of what Article 6 is?

Beatriz Granziera: Yes, absolutely. And I think just that question tends to get very tricky, very fast. So, Article 6 of the Paris Agreement is a framework that allows countries to work together to meet their mitigation targets more cheaply and effectively.

And with that, hopefully, to raise ambition. There are three ways in which countries can do that. So I’m going to very briefly just talk about them. Two of them are market-based and one is a non-market approach.

So the first market approach is called Article 6.2. This is not a great name, but this is just how it’s known. Article 6.2 sets rules for countries to cooperate directly—typically through a bilateral agreement. It’s a direct relationship between countries—through a bilateral agreement, for example, or even between a country and a company. And because it’s a direct relationship, there’s a lot of flexibility from the buyer and the seller to decide what they want to trade and how they want to trade.

The second mechanism, it’s called Article 6.4 or the Paris Agreement crediting mechanism. And that’s different. So this is a centralized system overseen by the United Nations. And it’s very similar to what we had in the past in the Kyoto Protocol with the Clean Development Mechanism. Because the UN centralizes this mechanism, it decides what methodologies are eligible, what sectors are in, what sectors are out and what rules apply.

And then third, you have the only non-market approach under Article 6, which is called Article 6.8. And it’s basically around climate finance. So the main point here is that there are no expectations of trading of carbon credits. And this mechanism is way, way less developed than the market track. So I’m not really going to focus on that here.

But before we move on and before we get into the individual components of Article 6, I think it’s important to take just a quick step back to understand what Article 6 means in a broader landscape of carbon markets. Because today you have several different markets that work in parallel. So you have the voluntary carbon markets where companies can purchase carbon credits to meet their voluntary climate targets. You have a lot of domestic compliance markets. You have some international markets such as the aviation market or CORSIA, you have Article 6. And what’s very interesting about this moment that we are living right now is that the lines between these markets are blurring more and more. So they are continuing to function in parallel, but more and more one market is influencing the other and they don’t work in isolation anymore. So to that question, what is Article 6? And when we talk about this, I think we can no longer assume that Article 6 is just another technical rulebook under the UN because now Article 6 is really a mechanism that sits at the center of the super complex landscape of carbon markets. And it’s already influencing how these other markets are evolving.

Arvid Viaene: So thank you. So if I were to summarize it, it’s you’ve got several of these markets, you’ve got the voluntary carbon market, you’ve got the aviation one, and now Article 6 is like the new player in town. And it’s already starting to shape the other ones. And then in Article 6, we’ve got Article 6.2, which is kind of buy, a It’s kind of a relationship between two parties. And so it’s kind of or like companies, countries, and it’s more flexible. And then you’ve got Article 6.4, which is the centralized system. So UN rules apply and govern the carbon offsets.

Beatriz Granziera: Yes, exactly. I think you nailed it. So one is very flexible. of course, you still have to follow some rules like, and sorry, So yeah, exactly. one is way more flexible and allows countries and the buyer and the seller to have a lot more flexibility to decide again what they’re going to trade.

And Article 6.4, because you have that centralized UN body, which is called supervisory body, then it’s basically you have to follow the rules that this body sets. So I think just some countries might want to move faster and want have more flexibility, might choose to go with Article 6.2. Other countries want that standardized credit with a UN stamp, that hopefully get where guarantees quality. So they might go with Article 6.4.

How Paris differs from Kyoto

Arvid Viaene: And that leads me to the next question is that think the prior interview Ben Probst, he was looking at carbon offsets under the Kyoto Protocol. Now we’ve got the Paris Agreement., what has changed in this Paris Agreement versus the Kyoto Protocol with the clean development mechanism?

Beatriz Granziera: There are a few very big shifts there since Kyoto. So first, right, Kyoto was just one centralized system, the Clean Development Mechanism, very similar to what I just mentioned around Article 6.4. At the time, we also had this centralized UN body controlling everything related to the operationalization of the Clean Development Mechanism. But under the Paris Agreement, as I mentioned, countries have a lot more flexibility to decide how to engage in markets, for example, through just signing a bilateral deal under Article 6.2.

Second, and I think this is a really key difference here, that under the Kyoto Protocol, only developed countries had binding targets for climate. That means that developing countries could then sell carbon credits without that really affecting their national accounting. So as a result, double counting was not really a concern back then. But this is different now under the Paris Agreement because every country has a mitigation target or an NDC, and that basically changes everything. So If a country sells a carbon credit today, it has to adjust its own emission balance to make sure that the same emission reduction is not counted in another country at the same time. Because if you’re counting one emission reduction twice, that won’t help as the goals of the Paris Agreement. And then that has some major implications that we get can get more into later. But now developing countries have to really think what kind of credits they are selling and what quantities and at what price.

And just, I’ll say that the third big difference here, a little bit related to what I’ve already mentioned, is that the landscape of carbon markets today is way more complex than what we had under Kyoto.

Now you have more than a decade of experience with voluntary carbon markets and a lot of lessons learned from what worked and what really did not work. You have large scale forest programs generating credits for the first time. and on top of that, there are today over 70 regulated carbon pricing systems around the world, including carbon taxes and emission trading systems. So with countries, for example, like Brazil now entering the space. So Article 6 is both shaped by and shaping all of these markets as well. And the rules are also hopefully learning from all this experience that happened in the past couple of decades.

Arvid Viaene: Thank you. And I think it’s also worthwhile pointing out that this is something I learned that I wasn’t aware of is that exactly under the Kyoto Protocol, there were no targets for some of these countries. So they could sell credits without it impacting their goals. But now that has changed with the Paris Agreement. So the double counting topic that you can only use it once becomes really important. And I was even kind of surprised that this used to be the case. You could just buy credits that the other person then didn’t need to account for. So, yeah, first when I read that, I’m like, huh? But it makes sense that is now a goal. So, and then this double counting is, as I understand it, addressed in Article 6.4, which is kind of the centralized system, if I can call it that.

Arvid Viaene: Is that also there in Article 6.2 in this bilateral system?

Beatriz Granziera: Yes, it is. Article 6.4 and Article 6.2 both need tools in place to avoid double counting. This may sound simple and obvious, but it was one of the main sticking points in the negotiations for years. Article 6 is one of the many articles of the Paris Agreement, and it took countries almost a decade to finalize rules. Almost all other articles were largely agreed in 2018 in COP 24, but Article 6 is really complex and that issue around how you really address the double counting was at the core of very heated debates throughout all these years.

Arvid Viaene: Why was it so heated?

Beatriz Granziera: Because we were coming from the Kyoto Protocol. So developing countries, a lot of them still had some expectations that they could still sell credits without really that affecting their own climate commitments under the Paris Agreement. So, and I think there is, Kyoto was divided between developing countries and developed countries. So it took a lot of time for countries to transition to this new Paris universe.

And I think addressing the double counting for all countries is a key point of Article 6 and really the core of why this system can work. Because unless you have, all countries moving towards reducing emissions, the system just, it doesn’t make sense in this new reality that we have right now.

Arvid Viaene: Exactly. So, and I can also, imagining that the EU exactly has this as a big condition that you want to have this double counting or otherwise it won’t reduce global emissions. So...

How big is the Article 6 market today?

Beatriz Granziera: Yes, exactly.

Arvid Viaene: Just to get like a sense of what the market is before we dive into the further technicalities, could you just give us an idea of the size of these carbon offsets, like how have been generated over the past or the past five years? And I know might get complicated with like those issued under Kyoto and now, but just kind of getting a sense of the landscape.

Beatriz Granziera: Now, I think that’s actually a really important question because there’s a lot of buzz around Article 6 right now. But when you look at the actual market and what’s happening, you realize very fast that we’re just at the very, very beginning. Just to break it down, you have around Article 6.2, So the bilateral agreements, you actually have a lot of momentum. There are over 80 bilateral agreements that have been signed between countries to date. But then when you look at the actual trades between countries, the number falls to two. So only two trades have happened. One was between Switzerland and Thailand back in 2024. And the second one happened a few months ago between Switzerland and Ghana.

So this is a market that hasn’t really even started yet. So there are a lot of reasons why that’s the case. So first of all, after a decade or almost a decade of negotiations, a lot of countries are still regulating Article 6 domestically. And that’s complicated. That requires sometimes congressional approvals, different legislations, different, negotiations. So that just takes time. The second [reason] is that there’s a lot of uncertainty now about how countries will get to their climate targets. Just to explain, climate targets under Paris Agreement, they are updated every five years. And then the next target to 2030, it’s coming up, but countries are not absolutely sure yet where they’re going to be there. So they have to be careful about how many credits they want to sell under Article 6, because these credits will not be able to use for them to meet this climate target. So this is a very big component. And the third thing is that demand for Article 6 credits is still small and quite fragmented. So overall, Article 6 is up and running, but it hasn’t really turned into a liquid market yet. So to your question, like how many credits we’re talking in terms of supply, we don’t know yet.

And there are very few countries that have, the legal framework in place, the institutions in place and a pipeline of carbon credits that could qualify for Article 6.

Arvid Viaene: Thank you. And then I think that does stand in contrast to the voluntary carbon market, where I think one of the big things that I’m learning is this course, yeah, like the aviation is like a big source of demand for credits.

Could you maybe speak a little bit more to that? Because even in your projected demand for 2030, they were in there.

Beatriz Granziera: Yes, absolutely. So I was talking before about supply of Article 6 credits and how that is slowing happening. But then another huge component of any market is where the demand is coming from, right? Who is going to buy in the end Article 6 credits? So today, as I mentioned, Article 6 demand is not there yet. It’s fairly small, but it’s slowly emerging. So demand for Article 6 comes basically from two sides. One, you have buyer countries, mostly developed countries like Switzerland, Singapore, Sweden, South Korea, Norway and Japan. They want to use Article 6 credits to meet their own climate targets.

So these countries have announced some demand, and this is by 2030 200 million tons of CO2. But as you very correctly mentioned, the bulk of Article 6 demand comes from CORSIA, which is the aviation sector where companies would be purchasing credits to meet their own goals under this Corsia market. But I think there’s one thing that is important to mention here, that this is just, the numbers that I mentioned are just a photo of what we have today, and they will for sure change in the future. So as we get closer to 2030 and also closer to 2040, more and more countries might rely on Article 6 to meet their own climate targets.

And I think one of the biggest examples that we have is the European Union that announced just in December of last year, 2040 target, which allows of 5% of Article 6 credits. So that 5% might not sound a big number, but it’s actually a huge game changer for Article 6 demand. And just the EU alone could double all the current Article 6 demand that we have today to 2030. So that’s definitely going to be a big deal in how the market progresses.

Arvid Viaene: Could we talk about the EU demand just for a second? Because one of the things I was surprised by when I read your article is the timeline of the EU demand. So could you maybe talk about how they’re thinking of implementing this?

EU 2040 target and the return of international credits

Beatriz Granziera: Yes, absolutely. So, as I mentioned just last month, the EU finally agreed on their 2040 targets, and that’s a 90% reduction in emissions compared to 1990 levels. The big novelty here, as you mentioned in your introduction, is that for the first time in many years, the EU will allow 5% of this target to come from the use of international credits, and that’s basically Article 6 credits.

Arvid Viaene: Article 6.4, right?.

Beatriz Granziera: Article 6 in general,

Arvid Viaene: Got it

Beatriz Granziera: Yes, the EU, from what the EU has been announcing, it’s not yet clear. And I can talk a little bit more about the uncertainties that we have coming up in 2026 and the following years. But just in terms of timing, the use of international credits would be available from 2036 onward. And before that, you’d have a pilot phase running from 2031 to 2035. There’s not a lot of clarity on how the pilot phase is going to work. But that’s that’s just how the EU is structured. That’s the target.

And again, I think I want to emphasize this many times because, when you hear 5%, that might sound small, but politically it’s actually a big shift for the EU. Because for a long, long time, the EU has been very clear that it wanted to meet its its climate targets only with domestic mitigation inside the EU. So this decision to reopen the door to international creditS has definitely made the waves here in Brussels and well beyond.

Beatriz Granziera: And I can talk a little bit about the different positions here.

Arvid Viaene: Yeah. and Did it surprise you? Had you seen something coming?

Beatriz Granziera: Actually, it did surprise me when it first came. So these discussions, the first announcement came in July of this year. And we are used to see the EU in the Article 6 negotiating rooms, very clear that they won’t use these credits for, maybe, a decade of negotiation. So that was that was actually a surprise. But at the same time, the EU has been one of the main negotiators and decision makers in this process. The EU has been around the negotiation since the Kyoto Protocol. So on the other side, it makes sense that you might want to use, that is one of the flexibility mechanisms.

Arvid Viaene: Maybe we then, know, because they announced that some people were surprised and some people were against the use saying, we should keep all reductions domestic. I think there’s a case to be made to use credits from just a theoretical point. If you want, can reduce them somewhere cheaper. But there are then, of course, some worries. And I think one of the worries we talked about with Ben in his episode is what I would call flooding of past low quality credits.

Because under the Kyoto Protocol, you had these credits that sometimes were of lower quality or sometimes might have not mitigated CO2 or might have not reduced CO2. and now there’s this whole discussion as I get it about how do we transition those prior credits, if at all. So maybe could you talk about what the transition mechanism could you talk about what the transition mechanism is. Because I imagine those are also intense discussions.

Can old Kyoto credits flood the market?

Beatriz Granziera: Yes, absolutely. And you’re right. That has also been another important seeking point. So I think your question has two points there. one the criticism about the EU being open to the use of Article 6 credits in general. And the other thing, how this old Kyoto Protocol credits, and a lot of them, don’t have the same quality standards, would get into this mechanism. So I’ll just break it down and start talking about the criticism that we have been hearing here in process.

So I think one of the major concerns is whether relying on international credits would weaken climate ambition inside the EU or even risk increasing emissions domestically. Right. And I think that’s a very valid concern and definitely deserves serious attention, but I think this is only part of the picture because using Article 6 isn’t automatically good or bad, and it doesn’t decrease or increase ambition. What really matters it’s like are the details, right? And many of these details haven’t haven’t been decided yet. And this is what the Commission is going to start doing this year now.

So big questions that are still unanswered are: which sectors are going to be allowed, which methodologies? Is the EU going to use Article 6.2 Article 6.4 only? What safeguards will be in place? How will member states participate in the decision of how to purchase these credits.And, I think very importantly, what kind of buffers and quality controls will ensure that the credits coming in the EU are actually high quality and real and additional and verified.

And I think there’s also another point that I feel that is often overlooked in this discussion as well. By entering this market, EU is not only benefiting from the credit credits, but because the EU represents such a huge demand, it will also shape how the supply of credits will develop.

And right now, I mentioned before, we’re just at the beginning of the market. So supply has not yet been locked in. So the fact that EU is entering the market represents a big opportunity for Europe to shape how developing countries are developing the credits at what quality criteria with what ambition. And I think this is a very rare and timely opportunity that the EU have in the end, the EU participation could really drive more global ambition of this market, depending on how it’s done.

Arvid Viaene: Yeah. And in some sense, it’s because they then represent such a big potential demand, they can also have potentially more influence on the rules that go into it.

Beatriz Granziera: Yes, absolutely. Because, developing countries are looking at demand. So if there’s a clear demand signal to use, certain standards and, to have certain ambition, that’s how, where the market’s going to evolve. And the EU is one of the very few players in the market that has, the size and and scale to really shape all of this.

So I think this is, and this is like the side that I don’t feel it’s being talked about in Brussels that much, that the EU could have a huge influence on the quality of carbon credits that could then be developed in the future.

Arvid Viaene: And then we have the transition of the old credits.

Beatriz Granziera: Yes. So you’re right. The Clean Development Mechanism, some Clean Development Mechanism credits could transition to Article 6.4, but that’s there is one catch there. For most product projects, the deadline has already passed. So it was established in 2021 that like old projects from the Clean Development Mechanism could request transition until 2023, with the exception of afforestation and afforestation projects, which extended the deadline until 2025.

But then even when the project developer requests the transition, it’s up to the host country to decide if they will allow the transition. So this is a very important point. And this is one thing that was very discussed at COP30 in Bellin just a few months ago or couple months ago. That deadline for countries to approve the transition was extended by six months until June 2026. Without that approval, the transition won’t happen.

So if you look just in terms of how many projects requested transition, you have around 1,400 projects that could lead to, in the higher end, maybe a billion credits entering transition. maybe flooding at the Article 6 market. But in reality, the number of projects and credits that we transition will transition will be much lower because you require that host country approval.

Arvid Viaene: I think I read somewhere it’s like of the billion around 300 million would be allowed to enter or do I get that wrong?

Beatriz Granziera: Yes, I think that there are some estimates. I think the World Bank has come up with estimates around that number. But for me, when I talk to countries that are going through the very bureaucratic process of approving, the projects and people that have on their desks just a pile of projects that they are deciding to approve, I feel that this is still quite uncertain. Because a lot of countries, they still don’t know if they want to approve the projects for the reasons that I mentioned before.

If they approve the transition with a corresponding adjustment, that means that they cannot use these credits to meet their climate targets. So countries are being very careful. And I think it’s very hard to estimate how many credits are going to enter the market. The other important issue here is that it’s a market, right? So even if some credits from the CDM are allowed to transition, it’s up to the buyers to decide to buy them.

So if the EU, as you mentioned, like that concern that the EU would then be, buying CDM credits, that’s up to the EU. The EU can decide what kind of credits they will buy. And I think there is a big concern around quality on the CDM project. So I’m very curious to see how the market reacts to them and how much demand for these credits are and what price.

Quality control under Article 6.4

Arvid Viaene: So maybe that’s a good point to transition to Article 6.4 and the quality control on credits. Because as the way I read your explainer, it seems like there’s a lot of stringent quality control going on with the supervisory board. Could you talk more about what that supervisory board is doing and what the status is?

Beatriz Granziera: Yes, absolutely. And I think 2025 was a big year for Article 6.4 and the supervisory body. And everyone there worked really, really hard, including the UNFCCC Secretariat. So we had some very big milestones. For example, the first ever methodology eligible under Article 6.4 was approved just back in October for landfill methane. The first projects also started to transition.

Arvid Viaene: Just when you say it’s been approved for landfill methane, that means that every project in landfill methane meets all these requirements, it can officially enter in Article 6.4. There’s no more need for approval or like you would need some verification. Just what does that actually mean that now it’s been approved?

Beatriz Granziera: Oh, there’s a lot of approval. let me clarify: I think 2025 was a very big year for the Paris Agreement crediting mechanism or Article 6.4, with some very important milestones that the supervisory body and the UNFCCC secretariat achieved. Just to mention some of them, there were, for example, some very important rules that were draft. These are overarching rules around technical issues on permanence and additionality, leakage, baselines and all of that. Very important and very technical issues on how the market will work.

On top of the super broad and overarching rules, now they are also working to approve specific methodologies. So methodologies are basic, like, activity tailored rules that every project would have to apply to be eligible for Article 6.4. This will take time. The first methodology has been approved already. It was approved in October of 2025. And it’s just for landfill methane.

But now for 2026, the supervisory body will likely consider a lot more methodologies. So more projects and more types of activities can also be considered under Article 6.4. And then the other milestone is that projects already started to transition. So far, we don’t have any new project because we didn’t have methodologies until October, but we have some of those CDM-old projects that were that transitioned to Article 6.4. So definitely some very big moments for Article 6 right now.

And I think in terms of quality, this is a very key component because most of when you look at who is making these decisions, a lot of them were around making the same decisions under the CDM. So they, they [experienced the difficulties of the CDM quality control]. In fact, in many aspects, the quality issue was a big problem there. So you see that like quality control is a really big focus, as it should be. I think in general, it was a deliberate decision that one way to control quality is that to make very stringent rules. And with that, of course, you’re going to reduce the supply of credits that would be available to be generated.

So I think this is where we are right now. But I think there are other points to be considered in these discussions as well that were very, very evident and very important in 2025, because what you’re actually developing is a market, right? And a market needs to be feasible and needs to work if you want to deliver the goals of the Paris Agreement.

So if you implement rules that are really good on paper, but just they don’t work in practice, the system just won’t deliver mitigation and scale to meet the goals of the Paris Agreement. So I feel that right now you have that this tension between two sides. One side pushing to make rules very, very stringent and as they should be. But also some questions around to what point you pushed too much in a sense that you actually don’t deliver any of the goals that you are intended to deliver within a carbon market mechanism.

Arvid Viaene: So it’s like the balance between too stringent, it won’t generate any credits and then to lose you, you get a big concern about the quality. But right now, it sounds like if the rules get too stringent, there might just not be any, not, if the rules get too stringent, there might not be any credits. If, that’s a summary.

Beatriz Granziera: Just to give you an example, I think one of the biggest discussions of last year was around the role of nature-based credits within this market and how that would work. So, I think starting in the summer until the very end of last year, that was one of the biggest and most heated topics that I think it really went from, the super technical like policy nerd discussion to become a very big political issue. We had, Forbes, Reuters covering this issue. So it really became important. But basically, the supervisory body was drafting rules around permanence and the risk of reversals. And hundreds and hundreds of stakeholders in many countries raised concerns that these roles were so stringent that they would basically exclude nature from Article 6.4 altogether. And, as I was mentioning, this is not only about Article 6.4, because now all these markets are interconnected.

So this would really mean that nature would be affected in other markets as well, such as the voluntary carbon markets and other compliance markets. So I think this is an example of how, rules that might sound good on paper, in the end, could exclude one of the most important sources of supply. And nature is not only about reducing emissions, you have very important co-benefits for communities, for water, for so many other things. So, again , I think there are concerns around quality are important and they needed to be addressed. But I think risks should be addressed with risk management mechanisms, not only simply excluding full sectors from the market.

Arvid Viaene: It sounds like the rules might even get too stringent.

Beatriz Granziera: What I think is that the supervisory body developed some very important rules that are looking at quality controls. And as I mentioned many times, you cannot have a market if you don’t have very stringent quality control. So this is for sure important and this is what is wanted. But to your question on whether the supervisory body went too far, I think we don’t know yet because there are still a lot of rules that are going to be discussed in 2026, some very important components as well.

And I think to answer your question, we’re really going to have to wait until the methodologies are approved. So, as I mentioned, you have overarching rules, but like these discussions will come back over and over again when you when you approve methodologies.

All methodologies need to be approved by the supervisory body and all projects also need to be approved by the supervisory body. So these discussions will come back over and over again. And I think only then we will have a real sense of, how the market’s going to work.

Arvid Viaene: So, It sounds like the Article 6 is really like taking off like 6.4, the landfill methane was approved. Next year, we’re going to look at other projects. I think that’s my sense and takeaway is that this is all starting. This is all happening right now. Like it took a long time until COP29 to kind of agree on the things. And now it’s like starting to kick off for Article 6.4.

Beatriz Granziera: Yes, exactly. For Article 6.4, it has been a very slow development. So Article 6.4 is just now becoming operational for the first time. So, you haven’t had any trades yet. And this is, I think we only see how the market evolves when you actually have the trades. We will only see how stringent or how, feasible the market is when you actually start to have trades.

So I think I agree with you. This is a very exciting time to see how things evolve for, again, for a market that has the potential to be, a very big deal within the landscape of carbon markets and that is already influencing, how other markets consider high quality.

Arvid Viaene: Perfect, thank you for coming on. I think this is going to really help people get a sense of Article 6 instead of the abstract to actually get to know it. So thank you so much.

Beatriz Granziera: Awesome. That works. Great. Thanks, Arvid. It was really a pleasure to meet you and thanks So much for the invitation. It was great to participate here.

Arvid Viaene: When we think about tackling climate change, and given my training as an economist, I tend to think we should use either a cap-and-trade system or a carbon tax. But I recently read a paper that made me realize I might not be fully aware of the criticisms against pricing instruments coming from other disciplines.

So today I’m joined by Jeroen van den Bergh to discuss those criticisms—especially the idea that people might be boundedly rational. Jeroen is the author of a paper called Pricing Instruments in Environmental and Climate Policy when Polluters are Boundedly Rational.

Jeroen van den Bergh is an environmental economics professor. He is an ICREA research professor at ICTA-UAB in Barcelona, and an honorary professor at Vrije Universiteit Amsterdam. He leads ICTA-UAB’s Environmental and Climate Economics group, was Editor-in-Chief of Environmental Innovation and Societal Transitions from 2011 to 2021, and has received major honors, including the Shell Sustainability Research Prize, two ERC Advanced Grants, and an honorary doctorate in 2019. Welcome to the podcast.

Jeroen van den Bergh: Thank you for having me.

Arvid Viaene: This is a question I generally ask my guests: what’s the number one thing you’d want listeners to take away from your paper?

Jeroen van den Bergh: I guess that carbon markets—or emissions trading systems—are better than carbon taxes. Many people put them in the same category: they either like “pricing” or they don’t. But they’re actually quite different.For a long time, many colleagues were in favor of carbon pricing through taxes. Then I became rather indifferent. And now, after seeing the evidence for many years, I’m strongly in favor of carbon markets.

One main reason is that the biggest carbon market—another word is “emissions trading system,” or “cap-and-trade”—is the European one, which covers 30 countries. That’s already a big advantage. We don’t know any carbon taxation system, let alone other climate policies like standards or subsidies, that is harmonized among 30 countries.

In fact, it’s quite easy to extend the number of countries. It’s basically a technical “button” that can be activated and countries can be included. There have also been carbon markets across borders between Canada and the U.S.—different states and provinces have had joint carbon markets—which shows that country boundaries don’t matter very much.

And that’s great. You could not imagine a tax being shared across borders, because taxes are really national. They involve legislation, and rules about how revenue should be used. That’s very difficult to extend beyond borders.

2. Another reason I think carbon markets are successful is that they’re an institution outside the direct control of governments. Take the EU ETS—the European Union Emissions Trading System. When Russia invaded Ukraine, many energy taxes across Europe (and elsewhere) were lowered, cut, delayed—whatever.

The only system that remained intact, as designed, was the European ETS. At the national level, politicians couldn’t touch it. Also, many right-wing politicians who may not like climate policy were not even very aware of it, because it has been there for years. It’s a bit “hidden.” And that’s good—that’s what we need.

3. High prices: That leads to a third advantage.The ETS is the only system we’ve had so far that has achieved high prices. The carbon price in the European system has already exceeded €100 per ton—which is the order of magnitude we need. Maybe we need €200, €300, €400, but the order of magnitude is there. That’s very promising.

With carbon taxes, that’s very difficult to achieve. And if you look at carbon taxes around the world—maybe a dozen or so—and compare them with carbon markets, it’s clear carbon markets generally reach higher prices.

4. That’s probably because you plan the system: the cap goes down over time; the permits become scarcer and more expensive; and therefore the price goes up. That’s a big stimulus to reduce emissions, because polluters then face a choice: either emit and pay the carbon price, or reduce emissions. If the price is higher, they’ll adopt more expensive alternatives for abatement—and that’s how it works. But it also leaves freedom. Not every firm has to reduce in the same way. In some industries or subsectors, it may be very difficult and expensive to reduce emissions, so the system drives reductions toward those activities where it’s cheapest.

That’s a fourth advantage: it makes emissions reduction cheaper for society. It means the average cost increases in products and services will be less if you do it through carbon pricing. This point holds for carbon taxes too.

5. Automatic adjustments of the price: A final advantage is that we have economic growth and rebound effects. People may save energy, but then through behavioral and systemic effects they don’t save as much as expected; somewhere else energy use goes up; emissions go up. That puts pressure on emissions targets. With a tax, you’d have to raise the tax—which is politically difficult, if not impossible. Maybe you can raise a carbon tax once every few years, but if you do it too often you get voter and stakeholder resistance. Parties that don’t like the policy will use that to create resistance, win elections, and then get rid of the tax.

With carbon markets, if there’s more pressure on the system, the price automatically goes up—because it’s determined by demand and supply for permits. If there’s more demand, the price rises. Nobody has to decide it; no politician has to vote for it. The system arranges it itself.

So even with economic growth and rebound effects, the system responds. With taxation—and also with subsidies or standards—you don’t automatically control additional emissions from growth and rebound. They perform worse in that regard.

So my conclusion is: carbon markets are really the way forward. I know many people don’t like the word “market,” just like many people don’t like the word “tax.” So you can use the term “cap-and-trade.” Many environmental organizations accept that, because “cap” means you put a limit on total emissions, which aligns with a precautionary perspective. And it’s getting more support from environmental NGOs.

Arvid Viaene: Thanks for that. That was really helpful—and there was a lot in there. Let me process it. One thing your explanation made me realize is that with cap-and-trade, a lot is automated. Like you said: there’s no need for politicians to raise the tax because of shifts in the economy or circumstances; it just happens automatically through supply and demand.

And the second thing I took away is that it can be more “hidden,” in the sense that people are less aware it’s there—even though for a given price it can have a similar impact as a carbon tax. Is that right?

Jeroen van den Bergh: Yes, you’re right. A carbon market is an automated system, in the sense that politicians don’t need detailed information about emissions, technologies, or the costs of different abatement options.

If politicians try to decide, for example, “this sector must reduce X and that sector must reduce Y,” they need to know a lot: where are the emissions, what are the alternatives, how expensive are they? Historically, governments sometimes decided that sectors should contribute proportionally to their size or emissions share. That might feel “fair,” but it’s not a wise way to solve climate change—economists agree on that.

For instance: suppose agriculture is 5% of emissions, so you say it should do 5% of reductions. But if emissions reductions in agriculture are very difficult and expensive, why force that? You’d make food extremely expensive, and products depending on agriculture and forestry would become more expensive too. Society would see big cost increases, and that would reduce support.

With the ETS, we started by including big emitters. But it doesn’t mean they all contribute equally to reductions; it depends on their opportunities and costs. This increases the costs of things like metal, paper, fertilizer. We don’t know exactly how it affects final goods and services—and we don’t need to know every detail.

But if you had a carbon tax that was very visible in consumer products at the end of the chain, firms might start advertising: “We’re not responsible for this part of the price increase.” That’s not what we want.

Now, bounded rationality is also important—this is what we focus on in the paper. I think few people have realized this, so it’s quite innovative. If you have a carbon tax and you don’t get a good response because people are habitual, or they’re not very rational, or they don’t really notice the cost, then you get less emissions reduction than hoped.

But if you have a carbon market, and the response is insufficient—meaning emissions pressure pushes up against the cap—then the price goes up until the cap is respected. So the market automatically corrects for bounded rationality that would otherwise weaken emissions reductions.

That’s interesting because across the social sciences—including economics—bounded rationality is not the exception; it’s the rule. There’s a lot of talk about behavioral responses: defaults should be green; people should be nudged; car shops should show electric cars first, and only later combustion engines. I’m perfectly in favor of these things. But in my view, carbon pricing is the essence of the solution. The key question is: which type of carbon pricing is more robust to bounded rationality? For me, that’s carbon markets.

I already mentioned five advantages of carbon markets—this is a sixth. It’s a convincing list.

Arvid Viaene: I really agree with you that behavioral economics has become very popular—nudges, defaults, information campaigns, telling people how to reduce electricity use—but ultimately cap-and-trade handles a lot of that because you’ve set the cap. No matter how people behave, the cap is an upper limit for firms and there’s a limited amount of emissions permitted. So it affects the price such that the cap is maintained.

And in your paper you point to examples where giving people information doesn’t necessarily stick. There can be a lot of work in behavioral interventions, without a clear return.

Jeroen van den Bergh: Yes. I find it interesting because I’m looking back at an older paper where we discussed behavioral interventions and we identified six types of behavioral problems. I even have an idea for a new paper, because we didn’t really connect those six behavioral problems to carbon pricing—yet I think there could be a link.

In that older work, one category was inattention. You can use energy-efficiency labels and lifecycle information to create attention. But if you have a sufficiently high carbon price, that will draw attention—price information dominates behavior. If the price is very low, people ignore it. But if price differences between clean and dirty alternatives become large, attention will be there.

Another category is mental accounting: people have mental “budgets” for environment, energy efficiency, cars, and so on. Again, a higher carbon price can change that mental accounting, because people realize they’re hitting limits and must rethink.

Defaults are also important. But if the default is dirty and it becomes relatively more expensive because of carbon pricing, attention shifts toward the cleaner option.

Then you have present bias: people invest in an efficient car or heating system, but the benefits are in the future. With a carbon price, the energy bill is higher, and they more clearly see that future savings will be meaningful—so present bias is reduced somewhat.

Finally, there’s peer influence: people are influenced by others. Some see this as bounded rationality; others say it’s rational to rely on others when information is hard to obtain. Peer influence can complement carbon pricing. If pricing changes behavior for, say, the first 30%—the “first movers”—and others are socially sensitive, then social examples can reinforce the price signal. At some point you could get more than 50% changing behavior, which triggers a quicker transition. We have a paper on that. The advantage is you can need a lower carbon price if social interactions reinforce behavior change; we call it a social multiplier.

I also have a recent paper—published last week—extending this idea to a cultural multiplier. Social interaction is one thing, but sometimes people see themselves as apart of subcultures. (like seeing neighbors install solar PV). Cultural multiplier is broader: you’re part of a community or subculture—vegan eating, no holiday driving, low-carbon initiatives—so you’re influenced culturally.

That can also reinforce the effects of carbon pricing and allow lower carbon prices, which helps with political support.

The Use of Cap-and-Trade Revenues

Arvid Viaene: That’s a really good explanation of how those biases can interact. I also wanted to ask about something else I found interesting in your paper: how revenues are used. A lot of attention goes to whether we should do cap-and-trade or a carbon tax, and then revenue use is often an afterthought—even in textbooks.

If I summarize: if you set the price correctly, you’ve accounted for the externality, so you don’t necessarily need to subsidize green energy. But there may still be a role in developing new technologies. Could you elaborate on your thoughts on how revenues should be used?

Jeroen van den Bergh: Yes, it’s very relevant, because carbon pricing generates revenue. Carbon taxation clearly generates revenue. With carbon markets it’s not always as obvious, but in the initial phase permits are sold by governments, which creates revenue. You can also arrange the system so that permits must be renewed periodically—every year, every two years, every five years—possibly with a base price. That can create an additional revenue element.

Then the question is: what do you do with it? Surveys show people say they are concerned about inequality—people are inequality-averse. But when you ask people concretely how to allocate revenues, they don’t prioritize compensating inequality as much as you might expect. Instead, they tend to choose what we call environmental or climate projects. They like the idea: “use the money for climate projects.” Often they mean renewables. But it’s ironic: most renewable projects are done by private partners because they’re extremely expensive. People underestimate this. Tax revenues from carbon pricing wouldn’t be sufficient to fund massive renewable buildouts.

People sometimes point to cities like New York investing in renewables and say, “Look.” But compared to future needs, it might be a small share—maybe 5% of energy needs—so it’s not that impressive.

So why do people want “climate projects”? We haven’t fully sorted it out, but our guess is that many respondents think the main purpose of carbon pricing is to raise revenue and then use that revenue to solve climate change. But that’s not necessary. Carbon pricing already creates a price gap between clean and dirty alternatives, which stimulates firms, investors, and consumers to shift toward low-carbon options. That has an immense effect, and people underestimate that. People talk about “radical change,” but carbon pricing produces many gradual changes throughout the economy, and they add up to a radical transformation. Radical change is often many changes happening quickly. But somehow, people want to use that money to reinforce more change, and I understand that.

Now, subsidies can sometimes be useful, but not generally. Subsidies also create a gap, but differently: carbon pricing punishes the dirty alternative; subsidies reward the clean alternative. And we’ve seen subsidies don’t always work so well. There’s a study in Nature Energy that looked at 50 years of renewable energy in many countries. It found that only about 15–25% of renewable energy actually substituted for fossil fuels—depending on whether you look at electricity or broader energy categories. The rest largely met rising energy demand. That’s shocking. Some of that is due to demand growth. But it’s also because we don’t punish fossil fuels—we reward the clean alternative, which doesn’t guarantee substitution.

Carbon pricing would do better. I’m not against subsidies, but I’m critical of them. I think subsidies should be used to create a good market in early stages. Take Germany: it subsidized renewable energy over the last two decades—estimates vary, but on the order of €50 billion. Many experts now say: if we had spent that money on innovation, we’d be much further. What happened was: with good intentions, we tried to diffuse an immature solar PV technology to a large population too early.

Of course, it’s also not good to only innovate and not build markets. Markets have barriers too: production, sales, building integration, local government acceptance—many issues. If you have perfect technology but no market, you get delays. So you need to create a small market with subsidies. But we’re beyond that now—far beyond that—so I think subsidies are not necessary anymore.

Arvid Viaene: That helps a lot. I think you may have solved one of my open questions: why revenues from carbon cap-and-trade often go to renewable projects. It sounds like politicians do it because that’s what voters expect. People think the revenue is for funding the transition, instead of realizing the cap-and-trade mechanism is the solution.

In Europe, for example, EU ETS revenues used to be split—something like 50/50, where states could use some portion flexibly and some for climate projects. But I think it changed so that now it’s more like 100% must be used for climate transition purposes.

Jeroen van den Bergh: Yes, indeed. I think that requirement comes from frustration that we’re not solving climate change.The best way would be to raise the price more. But the EU is limited because it’s an open region; it can be competed away by other regions if it doesn’t protect itself. That’s why it’s working on the border tariff—the CBAM, the Carbon Border Adjustment Mechanism—which is not fully in place yet; it’s being experimented with.

Just to add to what you are saying, from a traditional economics perspective, revenues from carbon pricing should be returned to taxpayers neutrally, like a lump sum. “Lump sum” is a technical term: it means it doesn’t change behavior.

In practice, pure lump sums are difficult. But you could return revenues through income taxes, proportionally. If you give everyone the same amount, it becomes redistributive: poorer households get relatively more than rich households. You could do that if you want redistribution; if you don’t, you’d do it differently.

But we’re far from that way of thinking in policy. That economic principle—returning revenues neutrally—is not really followed. And that’s how society works: you need political and public support. And many people in parliaments don’t know this theory.

Arvid Viaene: I recently read a paper discussing everything about the ETS—framing, setup, and so on—and it barely said anything about how revenues are used. It surprised me.

Jeroen van den Bergh: There is good thinking on this. There’s a good paper in Nature Climate Change on how to make carbon pricing acceptable for citizens—“citizens” is in the title.

They present a scheme suggesting that revenue use should depend on country conditions: is the country prosperous or in crisis, is there unemployment, and so on. You could choose revenue recycling options that fit the economic and political situation and help build support. So there’s no single general advice. A pragmatic approach can make sense.

The potential progressiveness of Cap-and-Trade or Carbon taxes

Arvid Viaene: That connects to another point you raise: most people think a carbon tax is regressive. But you point out that in some countries it might be progressive. Could you talk about that?

Jeroen van den Bergh: Yes. This progressive nature is especially relevant for poorer countries, where a small share of the population has a luxury lifestyle and uses a lot of energy, while many people don’t even have access to electricity. Some households burn stoves using collected wood. Those people won’t be affected by carbon pricing directly.

There is a risk: people who use some electricity might reduce electricity use if it becomes more expensive, and switch to burning more wood. That could have negative environmental effects. Wood also emits a lot of CO₂ per unit of energy—if you rank fuels by emissions intensity, wood can be worse than coal. So developing countries are a special situation.

For rich countries, it’s more complicated. Studies for Europe found carbon pricing was not as regressive as expected. Maybe richer households don’t consume dramatically more energy than poorer ones, or maybe “poor” is relative and basic needs are still met. This leads to a difficult debate. Sometimes we say we must protect poor households—but poverty is a relative concept. Does everyone have a right to drive a car? Two cars? A flight every year, or multiple flights? If someone can only afford one car and one flight, are they “poor” in rich societies?

If someone truly can’t pay more, then with a carbon price it may become impossible for them to do some things. People then say carbon pricing is regressive. But is that what we should worry about most? These are sensitive ethical issues, and subjective. I don’t have a strong opinion, but I see people are afraid to touch them.

Arvid Viaene: Going back to criticism of pricing instruments: the EU ETS has been in place for a while, EU ETS 2 and CBAM are coming in. In Europe we seem to be moving toward more pricing. What do you think has shifted the narrative? Have papers convinced politicians, or is something else behind that trend?

Jeroen van den Bergh: Europe is different from other parts of the world, and Europe as a whole is also different from member states.

At the EU level, there’s a strong embrace of the carbon market. In all contexts, it is presented as the core pillar of European climate policy. Other studies show it’s the strongest element in national policy outcomes too. In some countries, you see small carbon taxes alongside the ETS, but they’re often low, and sometimes they replace existing energy taxes like fuel taxes. That’s good, but it doesn’t necessarily mean stronger behavior change, depending on design. I would invite all governments to replace existing energy taxes with carbon-based taxes or prices.

Many people don’t understand the difference. For example, fuel taxes aren’t proportional to carbon content. Different fuels—gasoline, diesel, others—are taxed in ways not directly linked to their carbon content. Diesel, for instance, can be slightly cleaner in CO₂ per kilometer because it’s more efficient—maybe around 5% cleaner than gasoline in emissions, depending on assumptions and lifecycle considerations.

The problem with diesel is local pollution: particulate matter, black soot. In cities, that’s not good. On highways, diesel can be better than gasoline. Diesel has a bad reputation now, and I don’t think it’s fully justified—but that’s a separate issue.

CBAM and Climate Clubs

Arvid Viaene: Right—and it’s like you say: if you change a general tax not related to carbon into one related to carbon, then these things get internalized. I’ve been following the CBAM, and it seems intellectually challenging: you have to estimate emissions embedded abroad along value chains. It’s a massive exercise, but once done, a lot happens automatically.

Jeroen van den Bergh: Absolutely. What the EU is doing—creating a protective border around its system through CBAM—is not perfect, because you need to estimate emissions from production of imported goods. You can’t know that perfectly. Companies importing goods are asked to get information from producers abroad, and they often don’t know exactly either. So there’s biased and imperfect information being used. But it’s a second-best approach—we knew that. The better solution is that the EU expands and invites other countries to join its system. This has already happened in a limited way: some countries that are not EU members are part of the EU ETS system, because the system allows it. There’s no real limit.

These are close countries: Liechtenstein, Norway, and I think Switzerland. You could go further: you could ask the UK. You could even go as far as certain U.S. states. The U.S. as a whole isn’t possible at the moment, but states bordering Canada, and states on the East and West Coast, are more progressive and trade a lot with the world. The EU is a major trade partner.

For them, it could be economically logical to join rather than pay carbon border tariffs. My proposal in some papers is that the EU invites other countries and also puts pressure through political channels. This is sometimes called a climate club or climate coalition that expands. I think this is the only way to solve climate change.

The Paris Agreement is not really an agreement in the strict sense. We don’t have a uniform harmonized policy; there are no punishment mechanisms. It’s more like a collection of voluntary bids. It’s good for communication, but every year at the COP meetings you see frustration that it doesn’t achieve what’s needed.

Big international agreements rarely start big. Trade agreements like the GATT and the WTO evolved over time. The EU itself didn’t start as a big organization; it started small—with the Benelux. Belgium, the Netherlands, and Luxembourg were the beginning. I could cross from the Netherlands to Belgium without a passport my whole life. That’s fantastic—and it’s where Europe started. We should learn from that: we won’t solve climate change with one big agreement. The Paris Agreement is fine, but it is not sufficient. We need in parallel, a coalition of countries with similar ambition that joins policy and expands over time. If China joined, for example—China has an ETS too, though it’s different—if China and the EU linked systems, that could make a big difference globally.

Arvid Viaene: Absolutely. It might also address a concern I’ve heard from Jos Delbeke: we might get short on liquidity in the EU ETS over time because we’ve used up lower-cost abatement options, and now we’re moving to harder-to-abate reductions. So we might get short on liquidity. Expanding could be in the EU’s interest.

Jeroen van den Bergh: Let’s do five or ten minutes more.

Arvid Viaene: Is there anything else you’d like to highlight about the paper, or anything we haven’t covered?

Jeroen van den Bergh: Not so much. I think we went through a lot of it.

Arvid Viaene: Then I do have one more question. What criticism do you hear most from non-economists—what are the common resistances to pricing instruments?

Jeroen van den Bergh: Good question. One thing people often stress—and economists are a bit at fault here—is that the main advantage of carbon pricing is efficiency or cost-effectiveness: it reduces the cost of emissions reduction. That’s true, but it can only be true if it’s also effective. If an instrument isn’t effective—if it doesn’t reduce emissions—then it can’t be cost-effective either.

But for me, something even more important is that carbon pricing, if done well, puts a price on fossil fuels proportional to carbon content. Coal becomes very expensive; oil less, but still a lot; gas less, but still. That creates a strong shift away from coal, and also from oil. Low-carbon alternatives like nuclear and renewables don’t have the extra charge, so they become more attractive.

Then, across the whole production chain and lifecycle, it stimulates movement away from high carbon. If you buy a product at the end of a long supply chain, it becomes more expensive if production didn’t shift away from high-carbon inputs. That becomes a strong incentive not to buy it. At the end of having implemented carbon pricing well, you can expect that cheap things tend to be low-carbon. “Cheap is good to buy.” Right now, it’s often the reverse: cheap is dirty. We shouldn’t make it too difficult. I don’t believe altruism alone will drive people to sacrifice a lot. People might buy green electricity at a slightly higher price, but not much—because your computer doesn’t run better on green electricity than on gray electricity. People will pay a lot for phones because they do new things. Green electricity doesn’t create a new function—it’s just a different production process.

And people have a limited willingness to pay. For me, the effectiveness of carbon pricing is guaranteed in a way that standards and subsidies are not. If you subsidize solar PV, people may buy it—but they’ll try to buy cheap ones, often from China, which can be “dirty” if there’s no carbon price. In China, production can rely on coal-based electricity.

Years ago, I tried to buy solar PV from Germany because studies suggested it was cleanest in production. It was very hard to find; much of what was sold in Spain was ultimately produced in China. I ended up buying mine from South Korea, which is based on nuclear energy, which is low-carbon. I don’t have a problem with that. So effectiveness is guaranteed by carbon pricing; not by standards; not by subsidies.

Arvid Viaene: That would be a great way to conclude.

Jeroen van den Bergh: I have one more point, related to free riding.

I stress in lectures that it’s extremely important to understand why climate change is so difficult to solve. Climate change is hard for many reasons. It’s abstract—nobody has “seen” CO₂. We have to trust scientific experts. I have that trust, but for citizens it can be difficult.

It’s also hard because our energy system is still largely dependent—85% to 90% worldwide—on fossil fuels, and there’s no quick way to replace them. Renewable energy is not problem-free either; much renewable energy is still produced using fossil fuels. But the most important problem, often neglected, is that climate is a free-riding problem.

Climate is what economists call a public good: many people can enjoy it; one person enjoying it doesn’t reduce others’ enjoyment; and if you don’t contribute, you can still benefit. If you don’t reduce emissions and others do, and the climate improves, you still enjoy the better climate.

That invites free riding. Individuals aren’t willing to sacrifice too much. People say they recycle and buy ecological products, but they won’t give up their car; they won’t give up flying for holidays. Carbon pricing counters free riding by putting a cost on the dirty alternative for everyone. It becomes easier to move away from it because you have an incentive.

Many alternatives suggested by people critical of pricing—subsidies, voluntary behavior, industrial policy—don’t guarantee reduction of free riding. And if you don’t reduce free riding, you don’t solve climate change.

Arvid Viaene: That was really good. I think I’ll clip that out too.

I want to give you a big thanks. I really enjoyed this conversation and learned a lot—not just from the paper, but from all the thought behind it. Thank you for coming on.

Jeroen van den Bergh: Thank you very much, Arvid, for your good questions—and your deep knowledge. It’s nice to have an interviewer who is well prepared and understands the issues. That helped me give good responses. Thanks very much.

Arvid Viaene: Thank you.

Let’s start with Measurement. As Peter Drucker said, ‘If you can measure it, then you can manage it.’ In episode one with Koen Deconinck, an economist from the OECD, we discussed measuring farm-level emissions. 10% of emissions happen at the farm level, but Koen pointed out that averages can be misleading because there’s a huge variety in emissions per farmer. One beef farmer might be emitting a lot, and another not at all. The challenge is how we can measure emissions at the farm level. We discussed many challenges and solutions in that episode. If you’re interested in learning more, I highly recommend checking that out.

Another episode where measurement was important was my interview with Ishan Nath, an economics professor at Harvard. Ishan’s work is about how climate change hits agriculture in the Global South disproportionately more. One of the insights is that climate damages are non-linear. Going from 20 to 21 degrees Celsius is not the same as going from 33 to 34 degrees. Crops start to wither away from temperatures beyond 30 degrees, so that baseline matters a lot. We also discussed why the Global South has a harder time adapting to climate change.

In episode three with Christa Hasenkopf, we widened measurement into air pollution. We discussed how measuring and publicly sharing pollution data often leads to political pressure. People are often not fully aware of how bad the air quality is. We discussed the case of China, where monitoring of air pollution helped make China’s clean air push visible and enforceable. She’s now helping set up systems to expand monitoring to other parts of the world where it’s not as developed yet.

Even in my episodes on cap and trade, measurement is often the first step, and it actually takes quite a long time to set up. Measurement is not just a nerdy topic; it’s part of policy because it changes narratives, accountability, and what becomes possible.

Let’s move on to the second category: Impact. This is where my solo episodes five and six live. In episode five, I provide a back-of-the-envelope way to think about climate damages. Simply saying ‘climate change is bad’ isn’t helpful for policy because policy requires trade-offs. In my rough calculation, a carbon price around 100 Euros per ton lines up with damages on the order of a few percent of output—my estimate was about 3.4% of GDP. We need a common unit to compare climate change to other urgent priorities.

In episode six, we discussed United States climate policy and the social cost of carbon. The social cost of carbon is essentially the damage caused by emitting one more ton of CO2 to current and future generations. In the U.S., this estimate moved from $1 to $190 per ton depending on the administration. Obama started a scientific process with the Interagency Working Group. Trump then changed some assumptions, reducing the estimate to $1. Under the Biden administration, incorporating new scientific estimates, it reached $190. In an ideal world, the social cost of carbon is a scientific estimate, but political factors often influence the final number used for policy.

Returning to air pollution impact, a remarkable statistic is that air pollution on average reduces global life expectancy by about two years. In New Delhi, this increases to about eight life years lost per person. In Europe and the US, we might think of air pollution as a co-benefit of tackling climate change, but in India and China, air pollution is the primary goal, and tackling climate change is almost the co-benefit.

In episode 12 with Joe Shapiro and episode 13 with Reed Walker, we asked if we are regulating air pollution efficiently at the margin in the U.S. They found that U.S. policy is still too lenient at the margin; further reductions in air pollution would provide more health benefits than it would cost firms to implement.

Now for the third category: Policy Design. Cap and trade markets are my favorite topic and the number one tool to tackle climate economics and air pollution. In a popular episode with Jos Delbeke, we had an institutional masterclass on building a cap and trade market. We discussed the creation of the world’s first market in the EU. It had many challenges initially, including over-allocation of emissions and over-supply of allowances due to the financial crisis and cheap offset credits. Policy is not static; they kept learning and developing tools like the Market Stability Reserve.

Going forward, it’s going to be a hard decade. We’ve done the easy-to-abate emissions. Upcoming work for the Commission includes the Carbon Border Adjustment Mechanism (CBAM) to get imports to pay a carbon tax and the EU ETS 2 for the transport sector.

In episode seven with Kaushik Deb, we discussed the world’s first cap and trade market for particulate pollution in Gujarat, India. In a randomized experiment, they found that while one-third of firms were not complying under traditional ‘command and control’ regulation, non-compliance dropped to zero in the cap and trade market, at a lower cost and with lower emissions.

In episode four with Ben Probst, we discussed carbon credit offsets—where one country buys reductions from another. While theoretically great, Ben’s paper examined 20% of all carbon credits and found that four out of five were essentially useless. Only one in five actually led to a reduction in CO2. There’s a serious credibility issue regarding these offsets.

In episode nine with Marian Krüger, we discussed carbon removal technologies. Costs vary a lot but are generally high, from $150 per ton for biochar to over $1,000 for direct air capture. We will likely need policy-driven demand from compliance markets like the EU ETS to continue attracting investment and innovation.

Finally, we focused on policy politics. In episode eight, Professor Lorenzo Cimarchi discussed the 2018 US-China trade war. China incentivized provincial officials to relax environmental standards to soften the economic blow of U.S. tariffs. While air pollution worsened, it didn’t significantly affect economic growth or competitiveness. In episode 14, Professor Matilde Bombardini discussed how extreme weather shocks impact voter behavior. Eight additional extremely hot days can shift the Democratic vote margin by about 0.66 percentage points, potentially impacting close elections and the probability of passing carbon pricing bills.

That was an overview of the episodes with some highlights. I hope you found this useful. In the next episodes, we’re returning to regular interviews, including one on the differences between cap and trade and a carbon tax, CBAM, and Article 6 on carbon offsets. Thank you for listening and have a great end of your year.

Transcript

Arvid Viaene: We talk a lot about the “right” climate policies, such as carbon pricing. But there’s a step before all of that: politics. Because you need politicians to carry out these policies. An who gets elected is decided by voters and their preferences as well as the positions of politicians. And these are likely to change when the climate gets hotter and the economy starts to transition.

So today’s episode will tackle these in the context of climate policy in the U.S.. In particular, you will be answer the following questions at the end of the episode

1. When a place experiences unusually extreme heat, does it measurably shift votes?

2. How do local green and brown jobs shape climate politics?

3. And how do those forces influence the probability of future climate legislation being enacted?

My guest is Professor Matilde Bombardini, and we’re discussing her working paper “Climate Politics in the United States.” What makes this research stand out is the data: precinct-level election results—so we can compare neighborhoods within the same congressional district—and detailed measures of candidates’ environmental policy positions.

Matilde holds the Oliver E. and Dolores W. Williamson Chair in the Economics of Organizations and is Professor of Business and Public Policy at UC Berkeley Haas, affiliated with NBER, the BFI’s IOG group, CEPR, and CESifo.

So let’s dive in. Matilde, welcome to the podcast.

Matilde Bombardini: Thank you so much for having me.

Arvid Viaene: I’m very excited, as I said. In previous episodes we’ve covered the impact of climate change and how to address it cost-effectively through tools like cap-and-trade. But this is our first episode that really analyzes climate policy from the perspective of what drives it through voter behavior.

So maybe just to start off: what got you interested in this project, and what were you trying to do?

Matilde Bombardini: Sure. I should start by saying that the idea that voters react to climate shocks is not new. We’re not the first to think about this. There are other papers that look at, for example, the effect of climate shocks on beliefs and use survey data to measure that.

What’s really unique about this paper is that we have very comprehensive data on voting. So it’s not just about how people’s beliefs respond to climate change; it’s about their actions – how they actually vote. At the end of the day, that’s what determines who gets elected.

We wanted to understand how different aspects of climate adaption and climate affect both voters’ behavior and politicians’ behavior. You can think of voters as the demand side of a political market, and politicians as the supply side: they “supply” policies.

The occasion came when one of my co-authors, Nicola Longuet-Marx, had completed a large data collection effort for the U.S. I’ll go into more detail later, but essentially this gave us very granular data in the U.S. So we could ask questions like: how does climate change itself – weather shocks – matter, and how does the climate transition matter – the changes in labor markets associated with the transition? Because we can measure these things at a very granular level, we can be satisfied with the answers we get, as we’ll discuss.

Arvid Viaene: Exactly. I think that’s what’s so interesting about your paper: it looks not only at voter preferences, but also at how politicians react to them. It really treats this as a demand-and-supply market, which I don’t think people always fully appreciate.

Matilde Bombardini: Yes. The important point is that if you only look at voters’ reactions, you’re very constrained to an inevitably short-run effect. Voters react given the policy positions currently on offer and the politicians who are already out there.

But we know that politicians will also adjust. If we want to go beyond the immediate short run and think about the future, we need to model how policy itself is likely to evolve – and for that we need both sides of the market.

Our broad inspiration comes from integrated assessment models. I’m sure you’ve talked about these on your podcast: they close the loop between the economy and climate. Firms decide how much to produce, that generates emissions, emissions cause more climate change, which feeds back into the economy, and so on.

What’s missing in many of these models is the political block. Emissions lead to higher temperatures or different precipitation patterns; people experience those changes; but how does that translate into political reactions that move policy in a particular direction?

That political reaction block is missing at the moment in these IAM dmoels, and our hope is that this paper gives a way of modeling that part.

Arvid Viaene: That’s a very good point. In the paper you focus on two main measures of shocks. One is extreme temperature – these very hot (or otherwise unusual) weather events. The other is related to the part of the economy people work in: whether their jobs are “green” or “brown.”

For example, in Europe we had some really hot weeks this year, and immediately you see the costs. People become very aware of climate change when they’ve just lived through a summer like that. It becomes a lot more salient. So could you explain the measures you use for extreme temperature, and why they might influence voting behavior?

Matilde Bombardini: Absolutely. I’d also reinforce what you just said: when you’re experiencing that heat, if you ask people right afterward, there’s strong evidence that they say, “Oh my God, climate change is the worst problem we’re facing.” We wanted to check whether that kind of reaction persists when people actually go to vote. We experiment with different measures, but the goal is to capture variation in both temperature and precipitation. We look at absolute levels – is it a particularly hot or particularly cold day – but our main measure focuses on an extraordinarily hot day relative to the baseline, so how unusual the weather is relative to local history.

As you know, some places are always hot. We want to capture unusually hot days, so we define a day as “extremely hot” if it is more than two standard deviations above the historical average for that specific day of the year in that location. We then count, for each year, how many days cross this threshold – and we do the same for extremely high precipitation.

Arvid Viaene: Right, because it’s really hot in summer and then we get to winter. By the time you go vote, does the effect? You mentioned earlier that you weren’t sure whether the effect would persist. Did the paper convince you that it does – at least to some extent?

Matilde Bombardini: At the end of the day, we do find effects. We’re working with about the data that as good as it is going to get for the U.S. in terms of quality and spatial detail, and that’s important for being confident in the results.

When I talk about “granular data”, I mean that our unit of observation is the precinct – essentially the polling place where you go to vote. In the U.S., that’s roughly 1,200 people per precinct, and there are about 400 precincts in a typical congressional district. A congressional district is a single-member district that elects a member of the House of Representatives.

A lot of previous work, in the U.S. and Europe, is at a much more aggregate level – at the district or county level. If we only had data at the congressional-district level (or higher, like counties), it would be very hard to do the joint demand-and-supply analysis we do.

Why? With precinct-level data, we can compare different locations within the same congressional district that happen to experience different numbers of extremely hot days, holding constant who the politician is – their party, ideology, and other characteristics. So we’re observing at the smallest level and isolate the effect of the weather shocks themselves. There is some individual voting data out there, but only on turn-out basis.

Arvid Viaene: Yes, I really want to emphasize how granular your data are. I was very impressed reading the paper: you have this long period of time and very micro-level voting data. Politicians are complex: they have stances on a wide variety of issues, and you can now filter out a lot of that and zoom in on their climate positions. The way you do that in the paper is really impressive.

Matilde Bombardini: I should take zero credit for that part. This is all our young co-author, Nicolas Languet-Marx, who is going to join Berkeley next year and is currently a postdoc at Stanford. In his job-market paper he collected and assembled this voting dataset. You might think it shouldn’t be so hard to get, but in the U.S. elections are run by states and counties, and the data are stored locally. So he had to collect precinct-level results from hundreds of different sources and then harmonize them.

The other major data source he built is on policy positions. He uses both surveys of candidates and information from their websites and campaign platforms. Combining those, in a way that’s detailed in his paper, he constructs measures of each candidate’s positions along several dimensions: cultural, economic, and environmental. That is really what he did in his job market paper.

What’s amazing is that he gets positions for both candidates in a race. We already have good ways to measure the positions of incumbents – people who are elected and cast roll-call votes – but those are typically only for politicians after they are in office. To get the positions of both candidates before the election, you need this kind of campaign-based data.

Arvid Viaene: Exactly. And you also mention in the paper that the way candidates market themselves during the campaign is a good predictor of how they actually vote once in office. It is a credible signal. It’s not just cheap talk.

Matilde Bombardini: I’m glad you noticed that. Some people immediately think, “Well, this is just what they say; of course they’ll behave differently once elected.” But in the data, these pre-election positions are actually very good predictors of roll-call votes. So we take them as pretty good measures of policy stances.

Arvid Viaene: The other important measure you look at is green jobs versus brown jobs. Could you explain how you measure those?

Matilde Bombardini: Yes. At the same level of granularity, we construct measures of “green” and “brown” employment. You can think about the costs and opportunities of the green transition in many ways, but we chose a very intuitive one: how many people are likely to lose jobs, and how many are likely to gain jobs.

Measuring brown jobs is relatively straightforward. We focus on employment in oil, gas, and coal. Those are very easy to identify and measure. Green jobs are trickier. We could spend half an hour talking about different definitions, but in the end we try to capture jobs related to the green transition, electrification, and renewables.

So it’s not just people working directly in wind and solar. It’s also jobs related to replacing power plants, upgrading the power grid, improving infrastructure, and a variety of ancillary activities. We follow definitions from the U.S. Bureau of Labor Statistics for green industries and occupations.

Arvid Viaene: I really recommend people check out the working paper, because you have some great graphs that show this visually. I might even include them when I publish this transcript. You can clearly see, for example, that Texas looks like you’d expect: there are a lot of oil and gas jobs, so more “brown” jobs that are at risk when regulation tightens. Naturally there’s more concern in those regions. I think we’ve covered the data, unless there’s something more you want to add.

Matilde Bombardini: We can always come back to it, but that’s the main idea.

Arvid Viaene: Great. Let me just sketch the structure of the paper for listeners. Roughly speaking, you first look at how extreme weather and green versus brown jobs influence voting behavior. Second, you look at how those changes in votes influence politicians’ positions. And third, you use those estimates to build projections into the future. So let’s start with the first piece: what are the impacts of extreme weather and green versus brown jobs on voter behavior?

Matilde Bombardini: We measure extreme temperatures as the number of “extremely hot” days in a year, in the sense we discussed earlier (two standard deviations above the historical local average). A one-standard-deviation increase in this measure – roughly eight additional extremely hot days in a year – increases the Democratic vote margin by about 0.66 percentage points. So if Democrats and Republicans were tied at 50–50, that shock would move the race to about 50.66–49.34.

For extremely high precipitation, we find a smaller effect – roughly half the size, about 0.35 percentage points for a one-standard-deviation increase – and those precipitation results are less robust overall.

If you think of both temperature and precipitation shocks moving together by one standard deviation, you get roughly a one-percentage-point increase in the Democratic margin. In a marginal or competitive district, one percentage point can matter a lot.

On the labor-market side, we measure the importance of green and brown jobs as employment shares. A one-standard-deviation increase in the green-job share increases the Democratic margin by about 0.2 percentage points, while a one-standard-deviation increase in the brown-job share reduces the Democratic margin by about 0.6 percentage points.

So the magnitudes are comparable and economically sizable, even if they’re not enormous. Many things affect voting, so we wouldn’t expect climate alone to explain everything.

Arvid Viaene: To summarize the temperature result: roughly one extra week of these extremely hot days – about eight days – translates into a 0.66-percentage-point shift toward Democrats. In a close election, that can really make a difference.

And on the jobs side, as you’d expect, places with more brown jobs are more worried about regulation, so that also has a sizable impact.

Matilde Bombardini: Exactly. We also tried to contextualize these magnitudes by comparing them to other known determinants of voting. One of them – and this may be less familiar outside the U.S. – is Fox News exposure, measured in minutes watched.

A one-standard-deviation increase in our extreme-temperature measure has a similar effect on Democratic vote share as roughly 2.5 extra minutes of Fox News exposure in the estimates from other papers. Those Fox News effects are very large, which is why such a small number of minutes shows up here as comparable.

We also compare our effects to those of partisan political advertising, and again, a standard-deviation change in advertising has a similar order of magnitude.

Arvid Viaene: When I first read that comparison – 2.5 minutes of Fox News – I remember thinking: that doesn’t sound like much, but given how powerful the media effects are in those studies, it’s actually huge at the margin.

Matilde Bombardini: That’s right.

Arvid Viaene: Earlier you mentioned persistence. Just to be clear: are these persistent shocks, in the sense that if people experience extreme heat this year, they’re still affected when they vote later on?

Matilde Bombardini: What I meant is that we don’t literally know whether someone remembers, say, “There were 12 extremely hot days last summer” when they vote a year later. Our estimates pick up the effect of weather shocks on voting when the election comes around. They’re not designed to track whether a person retains that memory in a psychological sense. So I wouldn’t claim strong “persistence” in that strict sense.

Supply-side respones ~19:00

Arvid Viaene: Got it. Let’s turn to one of the really interesting parts of the paper: how all of this shapes the positions of politicians. We’ve got climate change happening – and I’d assume anyone listening to this podcast accepts that it’s real. As we see more extreme days, people gradually shift toward voting more for Democrats, who, on average, have more pro-climate platforms. But you show some very interesting supply-side responses. Could you walk us through how you model that?

Matilde Bombardini: We model this in the simplest way political economists usually do: a spatial competition model in one dimension. The dimension is environmental policy: are you more or less in favor of ambitious climate policy? Candidates choose positions along that line.

Two forces pull on politicians. First, voters: each voter has an “ideal point” on that line, and candidates want to get enough votes to be elected. Second, their party or own ideology: they may have internal preferences – for example, a party platform – that pushes them toward a particular position. Politicians are solving a trade-off between appealing to voters and staying close to these internal or party preferences.

The complication is that when shocks hit – weather shocks or labor-market shocks – they affect both sides. Voters move, and politicians want to follow voters to win elections. But the shocks may also affect politicians’ own ideal points, perhaps through pressure from donors, activists, or the party.

So we need to disentangle how these shocks affect politicians’ final policy positions through these two channels. That’s what we do in the model and empirically. We estimate what happens to voters and what happens to policy positions, and then back out what part of the change in politicians’ positions is a response to demand (voters) and what part is a change in their own supply-side preferences.

Both parties react quite strongly to voters’ behavior, but in different ways, and it also matters whether the shock is a weather shock or a jobs shock.

For Democrats, start with the weather shocks. When you get a climate-related “popularity shock” – say, more extremely hot days that increase support for Democrats – voters move toward more pro-environment positions. Through that demand channel, Democratic candidates would like to move left on the environmental dimension to track their voters.

At the same time, when we look at their own supply-side preferences, we find that weather shocks push Democrats to moderate slightly – to move a bit to the right relative to where they’d otherwise be. One possible interpretation is that as they see climate becoming a more salient issue, they anticipate real competition on that dimension and choose somewhat more moderate positions rather than very extreme ones.

So for weather shocks, you have these two forces: voters pulling them left, and their own preferences nudging them slightly right. The net effect is relatively modest. For jobs shocks, when there are more green jobs, Democrats know voters will be more favorable to environmental policy, so again the voter-demand channel pushes them to the left.

But in this case, their own supply-side preferences also move strongly to the left. They may over-interpret the importance of green jobs, thinking, “Voters are going to love this so much that I should move very far toward ambitious green policies.”

We find that this overall shift to the left can actually be counter-productive for their electoral prospects, in the sense that they overshoot what would be vote-maximizing. That’s a potential lesson for Democrats – and for politicians in general – about not overreacting to favorable structural trends.

For Republicans, we find that their own ideological or party preferences are relatively insensitive to these shocks. The supply-side channel is weak. They do respond to voters moving. But here we find something that puzzled us for a while: when there is a pro-Democratic shock – for example, extreme weather that pushes voters toward Democrats – Republican candidates tend to move further to the right on environmental policy.

Our interpretation, which is consistent with the model, is that in some contexts Republicans essentially give up. Democrats become so hard to beat on the climate dimension that Republicans focus on signaling their ideological purity instead of trying to converge. They move away rather than toward the median voter.

Arvid Viaene: That result really resonated with some conversations I’ve had. A friend of mine in California said something similar: as a Republican, you might not want to compete with Democrats on climate if you think it’s a losing battle. You might actually double down and dismiss it even more.

Matilde Bombardini: Yes, that’s very much in line with how we think about it.

Arvid Viaene: Which may also help explain why Democrats can afford to moderate a bit on environmental policy: if Republicans move further away, there’s less direct competition on that dimension. Is that a fair reading?

Matilde Bombardini: It’s a good intuition, but it’s not exactly how our empirical model is structured. For estimation reasons, we don’t allow a candidate’s policy position to respond directly to the other party’s policy position. In our equations, Democrats don’t react to Republicans’ positions per se, and vice versa. They only react indirectly, through the observed vote margin.

So what we can say is that Democrats respond to how voters are moving, and Republicans respond to how voters are moving, but we don’t model a direct “I move because you moved” interaction between the two parties.

Arvid Viaene: That makes sense. You then take all these fairly complex voter and politician responses and plug them into climate projections. Earlier you mentioned integrated assessment models: temperatures get noticeably warmer over time, and that feeds into damages. Here, you let that warming feed into voting behavior, which then influences politicians’ positions. And you use that to run some really interesting simulations.

Could you walk us through what those projections say?

Matilde Bombardini: Yes. Once we’ve estimated the responses on both the demand side (voters) and the supply side (politicians), we embed them in projections of future climate and labor-market conditions.

Of course, you could imagine a complete realignment of U.S. parties that our framework wouldn’t capture, but conditional on the current party structure we can ask: if temperatures and green employment evolve in a certain way, what happens to votes and policy positions?

We take standard 2022–2050 projections of climate change under different socio-economic scenarios – we look at a more extreme pathway and a more moderate “business-as-usual” one that doesn’t meet the Paris targets.

Then we ask: under each scenario, how does the composition of Congress change, and what does that imply for climate policy? What we find is that, if nothing else changes, the composition of Congress becomes more Democratic over time because of these climate and green-jobs shocks. That’s the primary reason why we get more pro-environment policy in our simulations.

We translate that into a concrete policy experiment: we ask how the probability that the House passes a carbon-pricing bill, similar to the cap-and-trade proposal that nearly passed in the early Obama years, changes over time. Our estimate is that, under the more extreme climate scenario, this probability is about 9 percentage points higher in 2050 than in 2020. So if the probability was in the upper 60s in 2020, it would be in the upper 70s by 2050.

You can ask questions about this size – we’re not doubling the probability – but it is meaningful. People have reacted differently to this number: some find it encouraging; others are disappointed that it isn’t larger.

It raises a natural question: voters do react to climate change and green jobs, but do they react fast enough and strongly enough to really change the trajectory? That’s something we can’t fully answer, but the estimates give one perspective.

Arvid Viaene: I chose to read it in a somewhat optimistic way. An extra 9 percentage points, combined with other shifts, can move you from, say, a 45% chance to a 54% chance of passing a bill. And as you mentioned, a cap-and-trade bill like Waxman–Markey was already very close to passing once. So these margins matter.

Matilde Bombardini: Exactly. Even in 2020, the probability of passing such a bill is not zero, and an extra nine points can be pivotal. But, yes, we’ve definitely heard people say they wish the number were higher.

Arvid Viaene: And just to be clear, that 9-percentage-point increase is by 2050, right? Is that a roughly linear increase, or does most of the action come later, when climate impacts really ramp up?

Matilde Bombardini: Yes, that 9-point increase is by 2050. In our framework the effects are essentially linear in the underlying climate and jobs projections. So the timing depends largely on when the climate models forecast temperatures to rise and when green employment grows. So if the physical climate models show more change later in the period, that’s when our political effects also become stronger.

I should add that we’re currently working on extending the analysis to incorporate a more optimistic scenario for green and brown jobs. In the current draft we rely on BLS projections that are close to business as usual. We’re now adding a scenario with more aggressive electrification. So, for anyone interested, it may be worth checking out future versions of the paper.

Arvid Viaene: When you say that the Democratic vote margin increases by 9%, do you also translate that into a number of additional Democratic seats in Congress?

Matilde Bombardini: We mostly report results in terms of vote margins. Under the worst climate scenario we analyze, we find that by 2050 the Democratic vote margin for the House increases by about 1.4 percentage points. Under the more muted scenario, it increases by about 0.8 percentage points.

Arvid Viaene: Before we wrap up, is there anything important we haven’t touched on yet?

Matilde Bombardini: Yes, there’s one concern we’ve heard a lot, and I think it’s important. Someone might say: maybe when there are temperature shocks, people vote more for Democrats, but not because of climate policy. Perhaps heat is correlated with other things – like crime – that push people toward Democrats for other reasons.

We do several checks that make us much more confident that what we’re picking up is really about environmental policy. First, we run a kind of falsification exercise. Instead of using candidates’ environmental positions, we plug in their cultural positions. If heat shocks were just making people more likely to vote Democratic for generic reasons, we’d see effects there too. But we don’t: we find no corresponding effect on cultural policy positions.

Second, we interact the climate and jobs shocks with the distance between candidates in policy space. We find that the effects of the shocks on voters are stronger when candidates are further apart on the environmental dimension – but not when they’re far apart in other dimensions. Again, that’s what you’d expect if voters are responding specifically to climate policy.

Third, we look at a more narrowly focused type of election in two states, Oklahoma and Texas. There, voters elect commissioners who are directly in charge of energy and environmental regulation. These races are much more purely about climate and energy policy. We find similar patterns there, which reassures us that the effects we see are really tied to the climate dimension, not just “voting for Democrats because it’s hot.”

Arvid Viaene: I really liked that Texas and Oklahoma commissioner example, because those races are only about energy. There’s no other big ideological dimension that can sneak in. So for me the takeaway is that there’s an abundance of evidence that the effect is real and specifically about climate policy.

I would like to thank you for this conversation. I think people will learn a lot from this work. Some of my friends were already excited when I told them this episode was coming up. Thank you so much for taking the time and for giving us insight into the drivers of voting behavior on climate policy.

Matilde Bombardini: Thank you so much. It’s been a pleasure – and thank you for the very useful feedback for the paper itself. We’ll go back to the drawing board with some of your suggestions.

Arvid Viaene: Great. We’ll leave it there.

Arvid Viaene: Air pollution has fallen dramatically in the United States over the past half-century—but a harder question remains: are we regulating it efficiently today, at the margin? In other words, when we push pollution one step lower, do the added health and welfare benefits outweigh the added costs to firms and the economy—or have we reached the point where extra cleanup is no longer worth it?

This episode revisits that question through one of the most clever data settings in modern environmental economics: Clean Air Act offset markets, where firms buying the right to expand emissions must pay other firms to reduce them. Those transactions reveal real-world, marginal cleanup costs—market-by-market, year-by-year—allowing a direct comparison to leading estimates of marginal damages. The headline finding from the research Reed co-authored with Joe Shapiro: in most markets, marginal benefits still far exceed marginal costs, implying regulation is often too lenient on the margin—with notable exceptions like Houston.

If you listened to the earlier episode with Joe Shapiro, you’ll recognize the core idea and the same paper. But this conversation is different in emphasis. With Reed Walker, we go deeper into the economic intuition of revealed-preference cost measurement, why cost curves can still look surprisingly “low” even after decades of cleanup, and why certain places—especially Houston—break the pattern. We also broaden out beyond this one paper: Reed explains how cleaner air can shape outcomes decades later, drawing on his research linking Clean Air Act-driven improvements around birth to higher adult earnings.

My guest is Reed Walker, professor of economics and public policy at UC Berkeley and faculty co-director of the Opportunity Lab’s Climate and Environment Initiative. Reed’s work sits right at the intersection of environmental regulation, health, and economic opportunity. With that, let’s dive in.

Arvid Viaene: I’m very excited because today Reed Walker is joining me. Reed is a professor of business and public policy and economics at UC Berkeley. His research explores the social cost of environmental externalities—such as air pollution—and how regulations to limit these externalities contribute to gains and/or losses to the economy.

He is the faculty co-director of the UC Berkeley Opportunity Lab’s Climate and Environment Initiative. He’s also a research associate at the Energy Institute at Berkeley, a faculty research fellow at the National Bureau of Economic Research, and a research fellow at IZA. He received his PhD in economics from Columbia University.

So Reed, welcome to the podcast.

Reed Walker: Thanks for having me.

Arvid Viaene: I’m very excited to talk about air pollution because it’s one of my favorite topics, and I think it doesn’t quite get enough attention anymore. For those who didn’t listen to the episode with Joe Shapiro—or who can’t quite remember—could you give us a quick summary of your paper and what you found?

Reed Walker: Sure. Joe Shapiro and I have a recent paper in the American Economic Review exploring the costs and benefits of environmental policy in the United States—specifically, the efficiency of regulation.

When we think about efficiency from an economic perspective, we’re interested in whether the cost of regulation on the margin—the incremental cost of an additional unit of regulation—is equal to, larger than, or smaller than the benefits of that same unit of pollution reduction to society.

Quite naturally, you could imagine a situation where a regulation costs a billion dollars per ton to reduce air pollution. If the social benefits of that same unit of reduction were only a hundred dollars per ton, we might say that’s not really worth it from a social perspective. It’s way too costly for the benefits. So we’re trying to understand: on the margin, are the social benefits of better air equal to the private and social costs of regulating air pollution? That’s hard to answer because costs are often unobserved, and benefits are hard to measure too.

We explore a specific program in the United States under the Clean Air Act that requires firms that want to locate in certain areas to purchase permanent rights to emit pollution in those areas. Those purchases are useful because they let us get closer to understanding compliance costs. The intuition is similar to cap-and-trade markets: transaction prices can, through revealed preference, tell us something about how firms perceive the cost of compliance.

If the market price for pollution rights is extremely expensive—say, a billion dollars per ton—then a firm that wants to locate in the region will look for other technologies or ways to reduce its own pollution, so it doesn’t have to buy those expensive rights. But at some point, the firm’s own abatement becomes too expensive. If marginal abatement costs are increasing, then once they get high enough, and the firm still wants to locate there, it will buy the remaining amount it hasn’t abated on the open market. That tells us something about marginal incremental cost.

On the supply side, these permits come from incumbent firms. If an incumbent sees a market price of, say, a billion dollars per ton, and it can abate for a hundred dollars per ton, it might say: “I can make money here.” It can permanently reduce emissions, certify those reductions with the regulator, and sell them into the market—earning a profit.

So these supply and demand forces reveal something about costs on the margin. We then connect that to the best available estimates in the literature of the benefits of pollution reductions—on the margin—for specific pollutants.

One last point: we’re studying local pollutants, not global pollutants like greenhouse gases. The Clean Air Act regulates “criteria pollutants,” where damages are fairly localized. When we emit a ton of particulate matter, damages disperse, but they’re still relatively local. That means damages can be very heterogeneous depending on where emissions occur. A ton of pollution in New York City has much higher social costs because of population density than a ton emitted in, say, the Nevada desert.

So efficiency for criteria air pollutants is local: where damages are high, regulation should be more stringent. These offset programs exist in many cities across the U.S. and allow us to observe abatement costs on the margin in different places—LA versus Houston versus New York—and compare them to leading estimates of marginal benefits. That’s the paper in a nutshell.

Arvid Viaene: Awesome—thank you for that. I really like that explanation. The title of your paper is Is Air Pollution Regulation Too Lenient? Could you talk about what you find in terms of results? You compare the marginal costs to the marginal benefits—could you give an overview of the general findings?

Reed Walker: Big picture: I had a very diffuse prior going into this study. Air pollution in the United States has improved dramatically over the past 50 years—we’ve seen something like 90% improvements in ambient air quality relative to 1970 levels.

If you think abatement costs increase with the amount of abatement, you might wonder whether costs on the margin are now extraordinarily high relative to the benefits—whether that last 97–98% reduction is “worth it,” so to speak. But what we find is kind of the opposite. The marginal abatement cost identified in these offset markets is almost 10 times lower than our leading estimates of marginal social benefits, on average.

What’s cool is we can look across different markets and ask whether any places look over-regulated or under-regulated. By “over-regulated,” we mean a place where marginal abatement costs are much higher than marginal benefits. “Under-regulated” is the opposite: benefits are enormous relative to costs.

For the vast majority of markets, regulation appears too lenient—we could ratchet down further and move up the marginal abatement cost curve until marginal costs and marginal benefits are equal. But there are some markets—Houston in particular—where, on the margin, compliance costs look higher than benefits. There are some unique reasons for that, related to both costs and benefits.

Arvid Viaene: I want to come back to Houston because it’s a really interesting example. Overall, you find the marginal benefits of reducing air pollution are still substantially higher than the marginal cost of abatement. When you presented this to academics—or policymakers, or people in industry—were they surprised?

Reed Walker: I don’t know that I got very strong reactions, but I think people found it interesting that we now have a proxy for costs on the margin, and that we can estimate them in different places and at different points in time.

In the literature, it’s hard to point to a paper that estimates marginal abatement costs for criteria pollutants broadly. If it exists, it’s often for a specific industry in a specific location. So the ability to look across markets and over time is useful. It also raised questions for me about long-run versus short-run abatement cost curves. How can it be that we’re at roughly 90% reductions in pollution and marginal abatement costs still don’t look that high?

The answer has to involve technological change, induced innovation, or other ways to squeeze out further reductions at lower cost. But there hasn’t been a lot of compelling research on that, in my view—and it’s quite interesting.

Arvid Viaene: In the paper you also mention engineering estimates, like the ones the EPA has used. Did you find a noticeable difference versus those engineering estimates?

Reed Walker: There are engineering estimates for compliance costs that the EPA has developed internally. We looked at the software, the inputs, and talked to people at the EPA who use and develop these tools.

Ultimately, we came away dissatisfied with the quality of the estimates and the inputs being used. And if you ask EPA officials directly, they’re also unhappy with their ability to estimate these costs and keep databases updated. It’s incredibly complex. Information is scarce, resources are scarce. They’re trying to estimate the cost for a specific facility to install a specific technology—yet every facility is different.

There may be additional re-engineering costs that are hard to observe. And there are very few people trying to quantify engineering costs for essentially every facility in the United States. It’s just not practically feasible.

Arvid Viaene: Let’s come back to Houston. You mentioned it as a unique case where, for parts of the sample period, marginal costs can exceed marginal benefits. What’s going on there?

Reed Walker: Houston is a non-attainment area. In non-attainment areas—places out of compliance with the Clean Air Act—there’s a hard cap on stationary-source emissions of these pollutants. That means there can be no net increase in emissions. If a new facility wants to locate there, it needs a willing counterparty in Houston to offset emissions so the new facility doesn’t lead to a net increase, because Houston is out of compliance.

Houston is also a major petrochemical and refining hub. It’s close to the West Texas shale boom and can refine and process natural gas and oil from the Permian Basin.

With the advent of hydraulic fracturing—fracking—and strong production from West Texas shale, demand for expanded refining capacity skyrocketed in Houston, under a fixed emissions cap. When you get a huge increase in demand under a fixed cap and a fairly inelastic supply of offsets, prices spike. You see that in the data.

When prices spike, suppliers may get interested—thinking they can make money by supplying offsets—and you can see prices fall later, potentially reflecting supply responses. But the spike is very clear.

The benefit side is also unusual. The prevailing wind pattern is generally west to east. And east of Houston is largely the Gulf of Mexico (or Gulf of America, if you want to call it that). Fewer people are exposed downwind compared to other dense urban corridors, so damages can be somewhat lower than you might expect for a major city—because a lot of emissions get blown out over the ocean.

So Houston is a case where costs were high because of demand pressure from expanded petrochemical activity, while benefits were comparatively smaller because of where emissions tend to travel.

Arvid Viaene: Do you think Houston is unique, or could we see this elsewhere?

Reed Walker: I think it’s possible elsewhere. You need (1) a big expansion in demand and (2) fairly inelastic supply of offsets/permits. The inelastic supply is also related to how long an area has been in non-attainment. If it’s been in non-attainment for decades, a lot of the low-hanging fruit on the supply side has already been picked.

But if an area falls into non-attainment more recently, there may be a lot of low-cost abatement options—so more potential supply. So you could imagine similar scenarios in other locations if demand rises sharply under a fixed cap and supply is limited.

Arvid Viaene: Let’s talk about the benefit side. How did you estimate the benefits of air-pollution reductions?

Reed Walker: Joe and I did something deliberate: we didn’t estimate benefits ourselves in this paper. Estimating the benefits of air-pollution reductions is difficult, context-dependent, and sometimes controversial. Instead, we took “off-the-shelf” estimates from the frontier and compared them to our compliance cost estimates.

By “the frontier,” I mean integrated assessment models—most notably Nick Muller and collaborators’ AP3 model. These models combine inputs from economics and atmospheric science and then monetize damages.

The basic idea is a kind of source–receptor framework: if you emit a ton of pollution from a smokestack of a certain height in a certain place (say LA), the model uses information about wind and atmospheric processes to predict where it travels and where it lands.

Then it uses concentration-response functions to map changes in pollution exposure into health outcomes—morbidity and mortality—and then uses values like the value of a statistical life to monetize damages.

It’s a lot. But the technology portable: you can run simulations like “What’s the marginal damage of emitting a ton of PM in Seattle?” The model can include mortality only, mortality plus morbidity, and in principle could incorporate other channels like crop yields—depending on what’s included.

Arvid Viaene: That bridges nicely to your other work on health impacts. I wanted to ask about your 2017 Journal of Political Economy paper, “Every Breath You Take, Every Dollar You’ll Make: The Long-Term Consequences of the Clean Air Act of 1970.” What were you trying to do there?

Reed Walker: This started back in graduate school with fellow graduate students, when we were interested in an emerging literature—originating in epidemiology and picked up by economists—around what’s called the fetal origins hypothesis.

The idea is that the in utero environment can be particularly important and predictive for long-run wellbeing and later-life outcomes. There’s evidence from different contexts—famines, malnutrition, and other shocks—suggesting that cohorts exposed in utero can look different decades later in outcomes like IQ and other measures.

We were interested in exploring this in the context of air pollution, partly because there was work suggesting air pollution affects infant health—like foundational studies on the Clean Air Act and infant mortality. So we asked: if exposure to cleaner air around birth improves infant health, do those cohorts look different 30 or 40 years later?

The key for progress was data. We found data infrastructure developed at the Census Bureau, with linkages to the Social Security Administration, that allowed us to observe where people were born (county of birth), their exact date of birth, and link that to adult earnings from tax-related forms. That linkage let us take an existing research design used in earlier Clean Air Act work and connect it to outcomes measured 20–40 years later.

Arvid Viaene: What magnitude of impact did you find?

Reed Walker: From what I remember, it was on the order of $200 to $400 per year in earnings at around age 30. Cohorts born when air cleaned up substantially—relative to similar cohorts born in the same year but in places where air quality didn’t improve as much—had adult earnings that were a bit higher in that range. There’s a lot more in the paper about other outcomes and potential mechanisms, but that’s the basic magnitude.

I don’t think it’s an average effect for everyone, though. It’s more like an average of some people being severely affected and others not affected at all. But when you aggregate across the population, the total impacts can be large.

Arvid Viaene: One of the things that really struck me when reading this is, and I’ll even just quote from it: “Nevertheless, our estimates suggest that the long-run welfare cost of exposure to environmental toxins as measured by lifetime earnings losses may be as large or larger than the monetized costs of death based on short-run impacts of infant mortality, examined previous research.” So I imagine it’s just purely because of the scale of people being exposed to this, that it adds up to just this big amount.

Reed Walker: Yeah, I think that’s right. And I think that’s true more generally. There’s some interesting review work by people like Matt Neidell or Josh Kraft-Ziven, thinking about like the non-health cost of environmental externalities, maybe in terms of labor productivity or or other outcomes that are not directly, that may you know, tied to health, but are not direct health outcomes. And these are kind of typically on the margin, like a little bit smaller effects. But given the scale and the breadth of these impacts on society, when you start kind of wrap rolling these things up and and aggregating, they they become quite substantial.

Arvid Viaene: Joe told me you were the one who reached out to him about offsets—like, “Have you heard of offsets?” Finding the dataset is often a huge part of answering the question. Do you have any advice for researchers on finding the right data?

Reed Walker: I’ll give one piece of advice that’s a little flippant. Someone once told me: doing research is easy—you just need to know more about a topic than anybody else. And there’s a lot of truth in that. It’s hard for me to know more about returns to schooling than someone like David Card. But in energy and environmental economics, these can be relatively nascent literatures. You can read every paper on a topic quickly, and if you’re stubborn enough, you can dive into the institutional details and learn a lot.

Then questions start to pop up. Another approach is to think about what existing work couldn’t do—what held it back. In the fetal origins literature, for instance, some work used Scandinavian register data, and in the U.S. there were attempts using smaller datasets. The limited data held things back. So when we saw a county-of-birth variable linked to long-run outcomes, we realized it could open up a lot of questions people had been working on. There was also some luck: at Columbia at the time, people were actively developing the frontier of that literature, so there were ideas in the air.

One more thing: institutional detail really matters. But there’s an art to it. You can go so deep into the institutional weeds that your project becomes interesting only to one other person. The art is figuring out which part of the institution or research design is broadly interesting—something that transcends the niche and can support compelling causal inference.

Arvid Viaene: On that note—anything else you’d like to add, either on offsets or the JPE paper? Any takeaway we haven’t emphasized?

Reed Walker: Just that research begets research. These projects raise lots of questions that don’t necessarily fit in the original paper. When people ask where research ideas come from, a lot of the time it’s from other research projects. The hardest part is getting started. Once you start building an agenda, ideas begin to “fall out of the sky,” because you’re deep in the weeds and learning a lot—about tools, institutions, and the topic. It doesn’t have to be perfect at the beginning—just get started. Sometimes lightning strikes in a good way, and new ideas emerge.

Arvid Viaene: Amazing. Thank you so much for coming on the podcast.

Reed Walker: Yeah—thanks for having me. I look forward to listening and learning.

Is U.S. air pollution policy still too lenient – even after decades of regulation?

In this episode, I’m joined by Dr. Joseph Shapiro (UC Berkeley, NBER, Energy Institute at Haas) to discuss his recent research using 40 pollution offset markets under the U.S. Clean Air Act. By looking at how much firms actually pay for emission reductions, Joe and his co-authors back out marginal abatement cost curves and compare them to the health and welfare benefits of cleaner air.

We talk about:

• How pollution offset markets work in practice, and why they exist at all

• Using market prices (instead of just engineering models) to estimate the costs of cutting emissions

• Comparing those costs with the benefits of avoided mortality and morbidity

• Why, in most markets, benefits still exceed costs by a wide margin

• The outlier case of Houston’s VOC market – the “Taylor Swift of offsets” – where fracking-driven demand pushed prices through the roof

• What all this means for debates on whether air regulations are “too strict” or still too lax

If you’re interested in how economics, regulation, and air pollution intersect – and in actually quantifying the trade-offs – this episode is for you.

For questions, comments or suggestions, you can contact me at arvid.viaene.ce@gmail.com

Transcript

Arvid Viaene: Welcome to another episode with me, your host, Arvid Viaene. A key tool in environmental economics is the cost‑benefit analysis of policy regulations.

The idea is simple. For air pollution, the benefit of regulation is cleaner air; people are healthier and live longer. On the other hand, reducing emissions can be costly for firms, which increases prices and reduces output. In an ideal world, you balance marginal costs imposed by regulations with marginal benefits.

In practice, measuring both can be hard. In a recent American Economic Review paper, today’s guest, Joe Shapiro, tackled this problem in an ingenious way. Today we discuss his research and what it implies for whether air‑pollution policies in the United States are too strong or too lenient.

My guest is Joe Shapiro—associate professor of economics at UC Berkeley; research associate at the National Bureau of Economic Research and the Energy Institute at Haas. He studies climate change, air pollution, clean energy, renewable and exhaustible natural resources, and especially water pollution. His work links to international trade, public finance, and health. He holds a PhD in economics from MIT. Joe, welcome to the podcast.

Joseph Shapiro: Thanks for having me. I’m excited to be here.

Clean Air Act and Offset Markets

Arvid Viaene: I’m very excited about today’s topic. I’ve covered air pollution in China, India, and worldwide, but this is the first one on the United States. There are many interesting things in your paper. To start, could you give us an overview?

Joseph Shapiro: At a high level, we use a non‑standard approach to measure the marginal costs of air‑pollution regulation and compare them against the marginal benefits. We look at a component of the Clean Air Act that’s been largely overlooked in research. If a new polluting factory opens in a city, it must pay an existing factory in the same city emitting the same pollutant to decrease its own emissions.

These are offset markets. They’re useful for research because they include financial transactions where one firm pays another to decrease pollution. Those transactions help us understand marginal cleanup costs across cities, pollutants, and years.

Arvid Viaene: Why has this been overlooked by researchers?

Joseph Shapiro: The Clean Air Act is a defining piece of environmental legislation in the U.S. It’s been around for half a century and is central in environmental economics research. Many landmark papers study different features of the Act.

There are legal and policy studies on offset markets. Researchers for decades have called them among the most important components of the Clean Air Act’s use of market‑based mechanisms. The Act also has large cap‑and‑trade markets like the Acid Rain Program for sulfur pollution from coal or the NOx Budget Trading Program for nitrogen oxides in the eastern U.S. Why haven’t people looked more at these markets? A conjecture is that each market is a little isolated.

You might have a market for nitrogen oxides in San Francisco, another for volatile organic compounds in Houston. There are hundreds of these markets, but each is one region and one pollutant—smaller and more isolated than national markets like the Acid Rain Program.

They’ve also flown under the political radar. Big cap‑and‑trade markets are in the news; they change, get approved or shut down. Offset markets were reformed by the 1990 Clean Air Act amendments, but they’re not a major topic of political controversy and aren’t highlighted in most economics textbooks.

Another reason is data. Obtaining data is far from trivial. Most of the data we analyze have never been summarized or examined by academics, governments, or the private sector. Two states—Texas and California—have public disclosure laws for these transactions. For 14 other states, we purchased data from a broker who manages these transactions.

Lastly, many markets are decentralized: transactions happen firm‑to‑firm rather than through a central operator like an exchange. That makes analysis difficult because you can’t get a complete record in one place—you need to go to firms or intermediaries.

That’s one reason there are fewer papers with transaction data on decentralized markets, in any setting.

Arvid Viaene: It’s a really cool data collection. Economically, these offsets reflect the marginal costs nicely. As Steve Levitt said, once you see a great paper, you wonder why it hadn’t been done before—it’s a great paper.

Joseph Shapiro: Thanks.

How and Why Economists Compare Marginal Costs and Benefits

Arvid Viaene: Could you situate your paper in the literature? Much research focuses on the marginal benefits of air‑pollution regulation, not the costs.

Joseph Shapiro: Let me briefly clarify marginal costs and benefits. If a factory must decrease its emissions, all cleanup costs are costs of air‑pollution regulation. That includes installing control equipment like scrubbers; labor to manage it; materials; and less obvious costs, like decreased productivity of other activities.

Firms might produce lower‑quality products, face delays or uncertainty, change prices—penalizing profits and affecting consumers. All those are marginal costs.

On the benefit side, decreasing emissions improves ambient air quality, which affects health and welfare—reducing premature mortality, hospital admissions and other morbidity; improving child and in‑utero health, which may increase lifetime human capital and earnings.

It also affects firms—pollution can depress agricultural yields, increase capital depreciation, cause acid rain, and damage ecosystems. All those are marginal benefits. Much environmental economics research focuses on benefits. There’s been huge progress in strategies to measure the marginal benefits of air‑pollution regulation.

Researchers isolate causal effects; account for differences in health among affected populations (e.g., mortality displacement or “harvesting”); cast a wider net of benefits; and use strategies like land values, health, and migration.

However, methods to measure the costs of environmental policy have largely not changed in half a century. Researchers usually use engineering estimates—capital and operating costs of control equipment. Those are informative and easy to use, but have limitations: they’re not revealed preference; actual costs may differ; and they ignore other channels like delays, uncertainty, frictions, quality, and prices.

There are a few papers proposing other methods, but they’re not widely adopted and often measure total costs of broad regulations, not marginal costs of small changes. For optimal policy, we need marginal comparisons.

Arvid Viaene: Great explanation.

Joseph Shapiro: I taught this paper in my graduate class and presented it a few times. We also realized during writing that most progress has been in measuring marginal benefits; much less in widely adopted ways to measure marginal costs.

Arvid Viaene: One contribution of your paper is measuring marginal costs via offsets, allowing comparison with marginal benefits to judge whether it is too lenient or not. What did you find?

Joseph Shapiro: First, on benefits: many estimates combine how emissions affect air quality; how air quality affects mortality; and the valuation of mortality (the value of a statistical life). We take several leading models that make those calculations, and several estimates of the value of a statistical life, aggregating them to value mortality and health in dollars. We then compare those marginal benefits to marginal costs derived from offset transactions.

A benefit of our approach is granularity: different estimates of marginal benefits and costs for each pollutant, city, and year. Our broad takeaway: in most markets, the marginal benefits of cleaning up pollution are more than 10 times larger than the marginal costs. That suggests current regulation in these markets is too lenient—allowing more pollution than optimal because benefits remain large at the margin and costs are modest. Not every market shows this.

The clearest exception is Houston’s market for volatile organic compounds. It’s the Taylor Swift of offsets: demand is enormous, supply is limited, and prices become large.

In the late 2000s, hydraulic fracturing made U.S. natural gas prices low. Industries using natural gas expanded. Houston, a center for those industries, saw a boom in petrochemical and ethylene plants. Many large factories wanted to open, paying incumbents to decrease pollution and quickly marching up the marginal abatement cost curve. Low‑hanging fruit was picked; remaining opportunities were more expensive, while marginal benefits didn’t change. But that’s Houston; most markets show marginal benefits an order of magnitude larger than marginal costs.

How Do Models Put Dollar Values on Health

Arvid Viaene: That illustrates the upward‑sloping marginal abatement cost curve nicely. Back to marginal benefits: one thing listeners may not know is how you calculate them. How do you get from improved health outcomes—like mortality—to dollar estimates?

Joseph Shapiro: We use several models to ensure robustness. Each has similar structure. Suppose you emit one ton of a specific pollutant from a specific county—for example, volatile organic compounds from Houston. For non‑specialists: volatile organic compounds (VOCs) are dozens of chemicals that create ground‑level smog. If you spill gasoline and smell nasty fumes, that’s them—benzene, toluene, etc., which increase cancer risks.

The models ask: how does one ton of VOCs from Houston change ambient air pollution, not only in Houston but across Texas and the country, as wind and chemistry disperse pollution? Once we know changes in ambient air quality, we ask how that affects outcomes like mortality, morbidity, and crop yields.

We use concentration‑response functions from epidemiology and economics. We then assign dollar values to endpoints like mortality and morbidity. For mortality—the dominant component in dollar terms—we use the value of a statistical life (people’s willingness to pay to decrease mortality risk).

It’s often estimated from wages across occupations—for example, window washers on the 100th floor receive higher wages than those on the first; coal miners versus office workers.

We sum damages across locations, expressed in dollars, and call those the marginal benefit of abatement (or marginal damages of emissions).

One leading model, AP3, includes all those categories and finds mortality accounts for more than 95% of benefits. Our headline numbers include mortality; sensitivity analyses add other benefits, but they’re much smaller in magnitude.

[~17:21]

Engineering Models vs Offset-Based Costs

Arvid Viaene: Got it. Earlier you said engineering estimates aren’t revealed preference. How do your offset‑based estimates compare? Did you compare them to engineering estimates?

Joseph Shapiro: We did in earlier drafts and can summarize what we did even though it is not in the final version.. There’s a national engineering model called COST used by the EPA and several California agencies. It lists factories, power plants, and other sources; inventories installed pollution controls; and lists other potential technologies with capital and operating costs.

We compared offset prices (our revealed‑preference estimates) for plants engaging in transactions with what the engineering model says they could install and what it would cost. Our takeaway: the engineering model is all over the map, with little relationship to revealed‑preference estimates.

We examined the model and interviewed regulators and engineers. Major limitations include incomplete data on installed and available technologies; practical constraints (e.g., space, plant layout) the model ignores; recommending unrealistically cheap technologies that many plants already had; and outdated inputs (often from the 1980s). The final limitation was that many of the technologies were out of date, as many of the technologies were from the 1980’s, when the model was last updated and the situation on the ground was quite different. In specific settings, an engineer may know more about an individual plant than a national model. But national policymakers can’t send engineers in real time to thousands of plants; they rely on national models.

For illustration: nationally, for nitrogen oxides (NOx), decreasing emissions by one ton yields $40,000–$50,000 in health and welfare benefits. But offset prices show firms receive only $1,000–$4,000 per ton for NOx reductions. The incentive is too weak—society gains tens of thousands, but firms receive only a few thousand. Regulation is more lenient than optimal.

Engineering calculations show the same qualitative pattern (benefits > costs), but ratios fluctuate widely depending on market, technology, and plant.

Why has there been low awareness of the high marginal benefits? [21:50]

Arvid Viaene: You have established that the marginal benefits are still much higher than marginal costs. Why hasn’t there been more awareness that marginal benefits exceed marginal costs? Why not increase stringency?

Joseph Shapiro: Environmental economics is easy to teach partly because some policies sound crazy as written. For example, components of the Clean Air Act make it illegal to consider costs in assigning certain regulations, and courts have upheld versions of that. Some parts consider costs; many others say they can’t be compared. The goal from the laywers perspective wasn’t to equate marginal benefits and costs. They had lots of other goals, such as that it could be enforable and defensible. And in the 1970’s, the goal was just to bring pollution down. There also have not been a lot of comparisons of marginal costs and marginal benefits in the past

We also recognize policy is political. Changing stringency creates winners and losers. In the political economy spectrum, it is important that winners may be diffuse and unaware, especially the effect of decades of air pollution. There is the concept of a statistical life. When someone passes away, there is understandably an enormous amount of sympathy and sadness, but many 100’s of thousands dieing due to air pollution, it is often hard to say whose death was caused by air pollution, because the actual cause of death is not registered as air pollution, it is cardio-vascular disease, heart attack. In contrast, costs for firms are very visible. It’s harder to attribute specific deaths to air pollution, since death certificates list proximate causes. Political economy matters.

[~25:40]

Arvid Viaene: Earlier you offered to share how you and Reed started working on this topic.

Joseph Shapiro: Two sources. Years ago, Reed Walker and I had written papers on the Clean Air Act. He asked if I’d heard of emissions reduction credits—offsets where plants pay each other to emit. I hadn’t. Later I saw a news article about a plant investing in pollution reduction; it mentioned the plant earned a million dollars by selling credits. I looked into it and realized it was these credits.

I reached back out to Reed. Is this the market you talked about? We looked around, found California and Texas data, and it seemed like a gold mine: thousands of bilateral transactions where firms traded pollution for dollars—rare in environmental economics.

Environmental economics studies externalities—missing markets. When a market is created, we can observe prices and quantities, estimate demand and supply, and understand equilibrium. Finding thousands of transactions for air pollution at the heart of the Clean Air Act offered a natural way to learn about marginal costs, alongside existing measures of marginal benefits.

Arvid Viaene: You also interviewed brokers, buyers, regulators. Did you sense offsets were a deal‑breaker for entry or growth, given rising marginal abatement costs?

Joseph Shapiro: Anecdotes are mixed. Decades ago, people believed firms would just install controls and that’s it. Research has contradicted that. Research has shown firms respond on many margins: exit, avoid entry, switch products, use less energy, reduce output, fire workers, invest less.

In this market, we heard anecdotes of multinational firms considering entry, observing offset prices, and changing plans. Some of these plans were to make plants smaller to buy fewer offsets, enter markets with lower prices, or install extra controls. These are optimizing responses; whether they align with policymakers’ intentions is debatable. If decreasing pollution has large benefits relative to costs, a range of responses can be welfare‑improving.

Talking to policymakers, brokers, and Fortune 500 environmental managers is always revealing. I cold‑called every participant I could find in Houston one day. You learn market details and relevance. I always hold my breath when I do this, to see if how I characterized the market holds up. And every time it is reaffirming, but I do learn some details I did not know about.

Surprises and the Challenges for More Regional Regulations

Arvid Viaene: Anything that surprised you?

Joseph Shapiro: The magnitude and systematic differences between marginal benefits and costs were striking. Houston VOCs were exceptionally high, attributable to fracking’s indirect effects. I also hadn’t appreciated the lack of methods to measure marginal costs before writing this. Offset markets offer an appealing setting to learn costs. They have quirks and differ from cap‑and‑trade, but other environmental markets beyond taxes and cap‑and‑trade can also yield insights.

Arvid Viaene: Two final questions. One: in an ideal world, you could vary regulation by region. But regulation is set nationally. Would more geographic tailoring be ideal?

Joseph Shapiro: There are a lot of economics papers that look at environmental policy and say, wow, this is inefficient and suboptimal and poorly designed. Look at the crazy policies we have. That’s a very common type of conclusion. I increasingly feel that being cognizant of the political economy of environmental policy can add insight to those kind of conclusions besides just saying, hey, this policy is inefficient. And recognizing political economy, there’s a trade-off to allowing local policy It does allow for more flexibility that could tailor to local circumstances. It might also make regulatory capture easier. It makes political sway quite relevant. So local elections can sway policy back and forth. So a feature of the Clean Air Act is that it ties the hands of local regulators. If their air is polluted, the Clean Air Act does not give them a choice. They have to regulate more strictly.

And as this paper is trying to show, it’s doing it with a pretty ah rough tool, which is not perfectly tailored to be optimal. On the other hand, it’s certainly a welfare gain relative to doing nothing or weaker policy. And the more flexibility you allow, the more differences you may have in policy across jurisdictions.

In addition, on top of what the federal government is doing, many local governments have a wide swath of air pollution regulation. There’s a paper like from a couple decades ago that just looks at oil refinery, ah regulations of air pollution for oil refineries in Los Angeles.

And this paper counted more than 40 individual local regulations for oil refineries emitting air pollution. So that’s ignoring state and federal policies. It’s ignoring water pollution. It’s ignoring other industries.

So if there are, and Los Angeles is one of the most tightly regulated environmental settings in the country, but it’s not that every place is doing exactly the same thing. It’s that the Clean Air Act has some degree of uniformity and then local governments can add on top of it.

Many papers conclude environmental policy is inefficient or poorly designed. Recognizing political economy adds insight beyond that. Allowing local policy offers flexibility tailored to local conditions but risks regulatory capture and political swings.

A feature of the Clean Air Act is tying local regulators’ hands: if air is polluted, they must regulate more strictly. It’s a rough tool—imperfectly optimal—but better than doing nothing or having weaker policy.

Local governments also add policies. For example, Los Angeles once had more than 40 local regulations for oil refineries’ air pollution—ignoring state and federal policies and other pollutants or industries. The Act has some uniformity; locals add on top.

Arvid Viaene: That helps. As economists we want to optimize, but there’s a trade‑off between flexibility and regulatory capture. Final question: anything else you’d like to add?

Joseph Shapiro: The conversation is ongoing. Every five years, the federal government must evaluate evidence and decide if standards should be tighter. Then comes a Groundhog Day debate about jobs versus environment. The more we understand health and welfare consequences and the costs of control, the easier it is to assess trade‑offs.

This discussion will keep happening because the law requires periodic reevaluation. Other countries have Clean Air Acts with similar features; this isn’t just a U.S. issue.

Arvid Viaene: Sounds good. Thanks so much. Your paper helps us have more informed conversations. Thanks for taking the time.

Joseph Shapiro: Sure—thanks for reaching out and great questions. It’s fun to chat.

Timestamps:

6:55 - Getting Started in 2005: MRV And Sector Choices

12:14 - How The Initial Carbon Price Quickly Made an Impact

16:02 - Allocation Rules and Changes over Time

24:44 - The Collapse of EU ETS Prices - Financial crisis and Carbon Credits

28:28 - Solutions by the EU Commission to Stabilise Prices

32:41 -Key Lesson: The importance of having a good governance system

36:10 - Future Challenges and opportunities for the EU ETS

If you have any advice on how to improve the podcast or advice on future guests or episodes or ideas, please let me know. I’d love to hear from you.

The History, Challenges & Future of the EU ETS

Arvid Viaene:

On paper, climate policy sounds simple: you put a price on carbon. Either you tax it, or you cap it and let firms trade. In practice, doing that for one of the world’s biggest economies — as the first mover — is anything but simple.

This episode looks at 20 years of the EU Emissions Trading System (EU ETS): how it started, where it nearly failed, how it recovered, and where it’s going next. The ETS is the world’s first major carbon market, and it has helped drive CO₂ emissions in covered sectors down by more than 50% since 2005.

My guest is Professor Jos Delbeke. Jos is the former Director-General for Climate Action at the European Commission and one of the key architects of the EU ETS. He now holds the EIB Chair on Climate Policy and International Carbon Markets and served as the Commission’s lead climate negotiator in the run-up to the Paris Agreement.

By the end of this conversation, you’ll be able to answer three big questions:

1. Why did the EU choose cap-and-trade instead of a carbon tax?

2. Why were carbon prices so low for so long — and what did the Commission do to fix that?

3. Where is the ETS going now, as it expands to new sectors and pushes industry to decarbonize?

Jos Delbeke: My pleasure to be with you today.

Arvid Viaene: It’s a great honor to have you here. If listeners remember only one thing about the EU ETS — its origin story, its purpose — what should that one thing be?

Origins of the EU Emissions Trading System

Jos Delbeke: It started as a splendid economic idea. Economists wanted to contribute to climate policy and argued for economic instruments; there were many blueprints.

But having a blueprint is one thing. Implementing it in real life is another, because the world changes. Along the way, you have to make adjustments and adapt the system. You can’t have everything fully sketched out at the beginning. So the ETS developed gradually, which is why we had different phases.

Every five years, more or less, we reviewed the legislation—and that was very beneficial. Building a new element of climate policy took time to mature. Today we can say the system is in place and works fairly well. We have a solid price signal, and emissions are more than 50% lower today than when we started in 2005.

We’re now entering the next phase and a new discussion. With the war in Ukraine, moving away from gas as much as possible, big changes in energy, and an industry that still needs to decarbonize, the landscape for the ETS is changing again. That requires another review and rethink.

Arvid Viaene: Thanks for that. One thing this episode will show is that while there is a blueprint, there’s also gradual implementation and revision. People sometimes expect you can design everything from scratch ex ante—but that’s hard because of uncertainty.

Could you give us a broad overview of the different phases of the EU ETS?

Jos Delbeke: Getting started was the most difficult part. When people internationally ask me—Brazilians, Turks developing their own systems—my advice is: get started, and start with sectors where monitoring, reporting and verification (MRV) is easiest.

That was our important early choice: focus on the energy sector and manufacturing industry. Now, with ETS2, we’re moving into households, etc. But at the time we deliberately chose the big emitters, because tracking and trading emissions requires significant administration. You also need a robust compliance system. That was, and still is, demanding—so we began with energy and industry.

Another recurring challenge in the EU is competence: how far Member States let you go. We initially started with economic instruments and incentives, and first tried a tax—because that’s the obvious route. But taxation requires unanimity, which is very challenging in the EU.

From carbon tax ideas to cap-and-trade

After nearly a decade of trying a combined carbon and energy tax, we shifted thinking. Instead of defining the price, we defined the maximum quantity to be emitted—the cap. The cap declines over time and allows flexibility for operators.

That flexibility mattered because business had to come on board—and they weren’t spontaneously. But they disliked a tax. They were willing to try an economic instrument and incentives—anything but a tax. We could build on that engagement from businesses willing to act on climate. Industry cared deeply about cost‑effectiveness—reducing emissions at the lowest possible cost. The ETS was the perfect tool.

Political push: Commissioner Margot Wallström

We also had a good dynamic with Commissioner Margot Wallström, who immediately picked up the ETS. She was open to economic incentives and insisted we start the system while she was in office. So we set a firm timetable to launch in 2005.

That helped create momentum with businesses, NGOs, Member States and everyone else. We launched in 2005, before the Kyoto Protocol entered into force in 2008. That helped because of the uncertainty then. We described Phase 1 (2005–2008) as a pilot phase.

As a pilot, there was no banking of allowances from Phase 1 into Phase 2 (2008–2012)—the first Kyoto commitment period. That helped, because setting the cap required estimates, and Member States didn’t want to leave that entirely to the Commission. So that was a difficult exercise.

Building the Foundation: MRV and Compliance

We focused on MRV.(Note: Monitoring, reporting and verification (MRV)) You need companies to report emissions and a verification system so third parties can verify reports. Without trust in data, the market won’t function. So we were focusing on the essentials. On which elements did we have the most confidence.

Member States did most of the work and had a big say on the cap and allocation. Allocation was mostly free; there was no auctioning platform. Member States had an implicit concern to protect industry, creating an inherent tendency to inflate the cap.

Lessons from Phase 1: Overallocation of permits and need for better data

We were aware of that. What we didn’t foresee was that after the first year, over‑allocation was so clear that prices fell toward zero. That was a wake‑up call for businesses, Member States, and the Commission: when starting over in 2008, we needed much better data.

How did we get better data? By getting started. The MRV system established in Phase 1 became the perfect starting point for Phase 2. From 2008 onward we allowed banking because we had a much clearer picture of who emitted what. We had a great database—enviable compared with other environmental legislation at the time. It was that much better compared to other datasets at the time. So we used the pilot phase to set up the essentials. In Phase 2, the debate became more political—about the cap and the allocation process. Perhaps we can go into that later.

Arvid Viaene: One thing worth emphasizing: 2005 is twenty years ago now. IT wasn’t what it is today. It must have been a huge effort. It sounds like Phase 1 was used to get measurement and verification right so the rest could follow.

Jos Delbeke: Absolutely—that was the orientation of Phase 1. Phase 2 began real emission reductions. The largest reductions since 2008 have been in the power sector. Back then we had a lot of coal‑fired power generation. We gradually substituted coal with gas‑fired power generation. Fuel switching from coal to gas was supported by the carbon market and by decisions CEOs were making.

A psychological factor shouldn’t be underestimated: as soon as the ETS was agreed, CEOs knew they would have to pay a price for pollution. Nobody knew how high, but the fact of paying sunk in across boardrooms.

In the first period, prices were not bad—around €20–25—certainly better than later during the recession after the 2008 banking crisis.

That psychological element—you will have to pay for pollution—had an important impact. Companies, especially in energy, saw a way out: switch from coal to gas. When deciding on new power stations, invest in gas rather than coal. Europe’s reliance on gas was, in part, encouraged by the ETS because gas is less carbon‑intensive than coal.

Arvid Viaene: You’re describing CEOs becoming aware of the incentives, so they could plan and prepare.

Jos Delbeke: Exactly. Several companies began using an internal shadow carbon price for investment decisions. It was a guess where the ETS price would go, so they set their own benchmarks—€25 or €50 early on; later, many used €100 for internal planning. Expectations were factored into investments with lifetimes of 10–25 years.

Arvid Viaene: Let’s transition to 2008. There was the political discussion around reduction targets, and then the financial crisis hit. Could you elaborate?

Jos Delbeke: We had an important guiding framework: our Kyoto Protocol commitment for 2008–2012, which defined the EU’s overall effort. That overall effort was split between ETS‑covered sectors—industry and energy—and other sectors like households, heating and transport. In modeling, we carved out which part of the cap needed to be delivered by ETS sectors and which by Member States in non‑ETS sectors. That was easier in analysis than in politics.

Member States wanted a strong say in allocation rules, especially free allocation. In Phase 1, auctioning essentially didn’t exist—perhaps one or two percent of allocations where a Member State tried it.

During those years, criticism of the ETS grew, particularly concerning the power sector. The sector has minimal trade with non‑EU partners; it’s essentially European. Free allocation aimed to address competitiveness risks for trade‑exposed industries like steel, chemicals and cement—not power. The free allocation argument worked much more for the free market, but not for the power sector.

We observed that power producers were passing through the price of carbon allowances into electricity prices—even though they received most allowances for free. This led to a debate about windfall profits. The emerging consensus was that, in the next phase, auctioning should become the rule for the power sector.

That became the rule in Phase 3. Free allowances were limited to manufacturing. This was a major step forward, also because revenues could be used wisely. We created the Innovation Fund and Modernisation Fund, and most revenues returned to Member States. At that time, we couldn’t condition how Member States spent ETS revenues on climate purposes. They were keen to use revenues as they saw fit. Only later, in Phase 4, did a requirement arrive to use ETS revenues for climate policies—for innovation, home insulation, and more.

The real shift was moving the power sector away from free allocation to auctioning, and establishing common rules for free allocation in manufacturing. Through that process, we gradually Europeanized decision‑making for the ETS. Initially, Member States dominated. But auctioning largely escapes Member State discretion. We advocated for a common auctioning platform—eventually realized: the EEX in Leipzig conducts ETS allowance auctions. Member States were reassured they’d receive revenues without Commission interference, except for the innovation‑related funds. And that worked well. And that reassured Member States.

Harmonisation and a Single EU Carbon Market

Arvid Viaene: Switching from allocation (we can return to carbon leakage and CBAM later) to emission targets: as I understand it, in Phase 2 they were still set nationally, and in Phase 3 they became EU‑wide. Was that a gradual process? In Phase 1 there was over‑allocation and everyone was caught off‑guard by how much. What was the evolution from Phase 2 to Phase 3?

Jos Delbeke: The realization was that we had to implement our 2008–2012 Kyoto commitment to reduce emissions by a preset percentage—a common EU‑wide effort. We had to translate that into the ETS sectors versus those managed directly by Member States (households, transport, agriculture). The power and manufacturing sectors were increasingly viewed through an EU‑wide lens because we were opening markets—liberalizing electricity and building the internal market for goods and services.

These were the years of Jacques Delors and beyond, with the Single Market as the centerpiece of European construction. We brought that logic into the ETS, moving to EU‑wide coverage and a system that would gradually become fully harmonized—implemented by Member States, but harmonized.

This greatly improved cost‑effectiveness: on a wider scale you can chase the lowest‑cost reductions. So the wider the market, the more you get those benefits. Theory supported that. The UK had started debating a carbon market before the ETS, but the UK alone is a limited market compared to a large, liquid EU market. Denmark also attempted its own system, but it’s a small country relative to the EU market.

We were winning the argument for a single market for carbon allowances. That was creeping in gradually. Each time we tried to legislate it, it was easy to propose but hard to agree. In the end, we got there.

Oversupply After the Financial Crisis

Arvid Viaene: Let’s discuss the 2008 financial crisis. As I understand it, there was a drop in production and emissions, causing oversupply and downward pressure on prices. How was this experienced, and what steps did you take?

Jos Delbeke: There was a perception that prices were very low, and background grumbling about whether the ETS served its purpose at such levels. Two or three elements are worth adding. First, the industrial recession created an oversupply of allowances relative to the cap. Second, under the Kyoto Protocol, we had agreed that a fair amount of credits generated in developing countries could enter the EU. We did that expecting Russia, Australia, Canada, and the United States to participate in that international carbon credit market. In the end, they all pulled out, starting with the United States. And then those credits came en masse to Europe. So we had oversupply due to the recession, and on top of that, imports of carbon credits. Even with a low price, it was better to have a guaranteed price in the EU than nothing elsewhere. In the end, we imported about 1.6 billion carbon credits during the period the opening existed.

We acted on both elements. We asked the UN to tighten rules for credits because there were scams and irregularities—which they didn’t do, to my frustration. So we initiated the process to close our ETS market to credits from abroad. That debate continues today as to whether we should reopen to credits created under the Paris Agreement. That is another debate, I think we should do that. But at the time we needed to cut oversupply.

Stabilising the Market Price through the MSR

The second element—long in the making—was to put oversupply in a fridge, which we now call the Market Stability Reserve (MSR). We tried postponing some allowances that wouldn’t be auctioned, and similar steps, but only the MSR really did the trick.

The MSR defines a rule: when too many allowances come to market and aren’t absorbed, they go into the fridge and can come back later. A tool borrowed from financial markets, it worked fairly well. The night we reached agreement, prices began moving up from €5–6 immediately that night, to €25–30 in a couple of months. We left the low prices behind

European Green Deal and tightening expectations

Then came the European Green Deal, which strengthened expectations of a tighter cap. Prices rose from around €30 to €50, €60, €70, €80—with a record price of €100 in February 2023.

So the price recovery was due to closing the market to international credits, creating the MSR, and the Green Deal expectations. Those three elements explain today’s price levels. We also have a mild recession. Prices around €75–80 are a decent level given where we came from. A decent price works as a disincentive to pollute, and we see emissions going down. The incentive mechanism works. Some say the price should be higher; others complain it’s too high. I think today’s level is doing the job—that’s what matters most.

The Next 20 Years: Harder Abatement Ahead

Arvid Viaene: And by “doing the job,” you mean incentivizing companies to reduce emissions cost‑effectively within the EU pool.

Jos Delbeke: Absolutely. However, after 20 years of the ETS, the cheapest reductions have been realized. Over the next 20 years, the most expensive and difficult reductions lie ahead. That means we’ll need not only a relatively high carbon price, but also to avoid reaching climate targets simply by closing industry. We want industry to invest in decarbonized equipment. That’s the new challenge—captured in the Clean Industrial Deal—to accelerate and motivate decarbonized investment programs instead of importing more and closing activity.

Most reductions so far came from the power sector, with renewables coming in. The bigger task now is decarbonizing manufacturing—how to facilitate investments, deploy clean technology, and structure risk‑sharing and guarantees to enable investment decisions.

Governance Lessons for New ETS Designers

Arvid Viaene: Two follow‑ups. There’s a blueprint, then reality and surprises—lots of learning by doing. You’ve spoken with people in other regions. What lessons can others learn from Europe so they don’t have to experiment as much themselves?

Jos Delbeke: The most important—and most difficult—lesson is the need for good governance. You need solid MRV, and a strong central authority to set, decide and enforce the cap, with sanctions for cheating. When emissions equal money, there’s a risk of cheating—something we faced. Some allowances were stolen; operators were caught, jailed, and forced to repair the damage. That strengthened governance—for example, through a central registry held by the Commission to record ownership transfers accurately.

Good governance is essential, but it makes things complicated, which is why only strong governments have managed to implement ETSs.

China adapted our system to Chinese circumstances. Others are trying as well—Turkey is fairly advanced; Brazil and Indonesia are very advanced. There are always hurdles along the way. Establishing the system depends on good governance and a central authority that can impose rules and make it work.

Following governance is sound cap‑setting. Democracies must decide the rate of decline of the cap. Some want to go faster; others slower. That’s true in Europe—e.g., in current 2040 target discussions—and elsewhere. The cap needs to be clear to everyone. The payoff is reducing emissions at lowest cost while creating a business incentive for clean technologies. That’s the essence of 20 years of the European system.

New challenges for the EU ETS Future

Arvid Viaene: Final question. Prices are higher now and we’ve done the lowest‑cost options. Looking ahead, we have the Carbon Border Adjustment Mechanism (CBAM) and EU ETS 2—novel ideas the EU is pushing. Are lessons from past processes being incorporated, given cooperation with Member States, unexpected outcomes, and course corrections?

Jos Delbeke: Absolutely. International competition—particularly carbon leakage—will be crucial. From 1 January 2026, CBAM moves into real action. (Note: Carbon Border Adjustment Mechanism (CBAM)). It will be important to assess impacts, how it functions, and where to improve. This links to the carbon price. In the past we didn’t need CBAM because prices were much lower. Now prices are high and may rise as we pursue reductions higher on the cost curve. That raises liquidity and volatility questions.

We should consider the functioning of the Market Stability Reserve. It addresses overly liquid markets and too‑low prices. Perhaps we need to complement it for phases of insufficient liquidity and price spikes. The MSR merits a solid assessment: how well it worked and how it could be revised for a system tackling the remaining, more expensive reductions while navigating trade issues.

There’s the trade dimension: China exporting large volumes of clean technologies; the United States; and broader geopolitical changes. I mentioned gas availability from Russia—cheap Russian gas is off the table for Europe. Switching from coal to gas must be viewed in a completely different context now. So geopolitics—trade in energy and energy‑intensive commodities—will certainly be a consideration in the next ETS review.

Arvid Viaene: Jos, thank you so much for coming on. I really enjoyed this conversation and found it very insightful.

Jos Delbeke: You’re welcome. As you say, it’s a fascinating subject because the world around the ETS is constantly changing. That’s why I still follow developments closely and, here and there, try to inspire those doing the work with ideas and options for addressing various elements.

Arvid Viaene: This will definitely do that.

Transcript

Arvid Viaene: Today I’m trying a new format: a research-focused best-of from three earlier episodes. Air pollution remains a major public-health and economic issue in the world’s two most populous countries. Instead of a single narrative, you’ll hear a comparative analysis: first, the global health and exposure context; then the institutional mechanics that delivered reductions. In China, central standards and monitoring were tied to performance incentives for local leaders—classic command-and-control with enforcement capacity. In India, a more decentralized system allowed states—like Gujarat—to pilot cap-and-trade for particulates, using continuous monitoring and permit auctions to discover lower-cost abatement and build compliance.”

Arvid Viaene: But first things first, let’s hear some global estimates of the impact of air pollution from Christa Hasenkopf, director of the clean air institute at the Energy Policy Institute of Chicago.

Christa Hasenkopf: Globally, we estimate with research we’ve done at EPIC that currently people are losing about two years of life expectancy due to air pollution and really just one specific type of air pollution, PM 2.5, which is essentially smoke. And that’s more than AIDS, malaria combined. And so it’s actually estimated that air pollution has the largest impact in terms of mortality and morbidity combined on public health, which is, I think, astounding. And then, depending on where you look across the world, it can be the number one driver of mortality, especially in countries in Asia and Africa. And then to your question of how, essentially, I think we all know it doesn’t feel good to breathe in pollution and we know it doesn’t feel good on our lungs and it can cause respiratory issues and long-term things like lung cancer. But something a little bit harder to realize without actually having yeah research is that essentially air pollution, especially PM 2.5 particles, these very tiny particles, you breathe them in, they get throughout your entire so body and every single organ can be affected, but it can cause heart attacks, strokes, COPD, and really exacerbates any other issue in your body as well.

Arvid Viaene: Let’s go from the global picture to a large-scale policy response. In China, public access to monitoring data helped put air quality on the agenda, and by 2013 the government declared a ‘war on air pollution.’ We’ll start there, then look at what changed on the ground.

Christa Hasenkopf: It was whoever at the State Department had programmed the information that goes went out to Twitter at the time, on an automatic basis. They never expected the air pollution to get above a certain level, so they had a jokey tag for the pollution levels when it got above this apocalyptic level, what it was called in the media. It was beyond index, and it had a very inflammatory phrase associated with it, and that made headlines, and I think that really got people’s attention. But I also think it was people having the app that pulled data that and saying, oh, wow, maybe I shouldn’t go outside right now. Oh, wow, it’s bad again. And then seeing it compared to various places, I think I think that was a big driver and gave it some immediacy.

Arvid Viaene: So this led to China declaring a war on air pollution in 2014 and leading to a lot of government decisions. Back to Christa

Christa Hasenkopf: That’s right. That’s right. It is. And it’s been stunning, about 40% reduction in the past 10ish years, which when we compare that to, say, for example, the U.S.’s progression, that’s been much, much faster and shows what can happen. In terms of how they did it, it to me, , it’s a perfect example of air pollution. We know how, technically, we all do know how to solve the issue. It comes down to social and political will. At that moment in 2013, there was an uproar, I guess, of political and social will. And it resulted in them declaring war on air pollution. It also meant that the government put forward a lot of resources monetarily to do it, and also political will to enforce policies that were quite strict. So moving certain industries outside of cities or placing them strategically where they’re not necessarily downwind of the of city and a population. It meant closing down certain coal-burning factories. It meant pretty stringent policies that they then had enforcement mechanisms to see through. And it also meant a huge expansion of their monitoring to make sure this was what they’re doing actually working. It also meant with that monitoring, the data was more open and so people could actually see what was happening.

China’s political structure and The Impact of the US-China Trade Wars

Arvid Viaene: In my episode with professor Lorenzo Trimarchi, we went into more detail to how China implemented incentives for local political leaders to hit the environmental targets. Let’s hear from Lorenzo:

Lorenzo Trimarchi: “And de facto, what I think is fascinating about the Chinese Communist Party is that more they are more organized like what we would consider a private corporation than a public administration board in Europe, because fundamentally they have these public officials that are more corporate executives with a performance contract. And they all compete in a tournament under which they will be selected for a higher level of power, based on some performance indicator established by the hierarchy.”

“Then in the 2000s, starting from 2008, we all remember with the Beijing Olympic Games, the pressure that the Chinese citizens were made on government to fight pollution. And in the 2010 year, we had this war on pollution declared by the Chinese government, and then environmental standards became more and more important for promotion.”

Arvid Viaene: Monitoring and enforcement only scale if local officials are rewarded for hitting targets. In our conversation with Prof. Lorenzo Trimarchi, we dig into how China’s promotion system made environmental outcomes part of local performance metrics.

Lorenzo Trimarchi: And this preliminary evidence and surprise was pointing at the trade world triggering an increase in pollution in China. Why is that surprising? Because as a trade economist, we tend to think about tariffs mainly as a negative income shock, especially for developing countries. So we expect, okay, China is a country heavily specialized in the manufacturing. If we give a large trade shock, we expect China to reduce income and therefore to decrease pollution.

Arvid Viaene: But that is not what Lorenzo and his co-authors oberved. So they digged deeper and found that the the trade-war had an impact on policy:

Lorenzo Trimarchi: We started to investigate if the trade war had an effect on environmental regulation. And the answer is yes. This is the most robust part of our paper. So environmental regulation seems to be affected by the trade war in a way that the trade war induced an easing in environmental regulation for China. So this is the first big result. A negative shock in trade policy seems to have negative effect on environmental emissions.

Cap-and-Trade Market in Gujarat

Arvid Viaene: That trade shock underscores how policy can adapt to economic pressure. India faces a different institutional landscape, more decentralized authority at state level, so solutions evolve differently. In Gujarat’s industrial cluster, regulators tested a cap-and-trade market for particulates, using continuous monitoring to turn limits into tradable permits. Here’s Dr. Kaushik Deb on how that worked.:

Kaushik Debb: “But knowing that this is a new solution and this is something that’s never been tried anywhere in the world— so the world’s first particulate-matter market, ladies and gentlemen, was launched and delivered in India and has been functioning for the last five years, as I said. To make sure that we were actually designing a solution that’s real and delivers answers and reduces pollution, we divided this industrial cluster into two groups.

So the control group stayed within the existing command-and-control regime, while the treatment group was put under a cap-and-trade scheme.

The biggest result— I think the biggest result that the regulator was most interested in— is the level of compliance in the market. In the command-and-control group, the level of compliance was about 64%. Which is really what the regulator wanted to solve for. Because in the market, the level of compliance was almost 100%. There was just one compliance period in which two industrial units did not meet their emission targets. And for the regulator, that kind of pretty much solves the entire problem, right? You are able to achieve 100% compliance to an environmental standard that you want to achieve.

What do the local people want? They want an improvement in air quality. And for every compliance period, the emission performance of the treatment group— the folks who were there in the market— their emissions were lower by about 20% to 30%. So very significant and a chunky reduction in particulate-matter emissions that came from this particular experiment.

Arvid Viaene: Beyond compliance and lower emissions, a key question is adoption: do firms have a cost-based reason to prefer the market? Kaushik explains the cost side and why participation rose once results were public

Kaushik Debb: Now, how do we bring industry on board? You and I know this, right? Markets are an efficient tool. The whole point of efficiency is to reduce costs, to improve efficiency. And the folks in the market were able to meet their targets at a cost which was almost 11% to 12% lower than the folks who were there in the command-and-control regime. So there is a very clear incentive for industry to be in the market, which kind of is also evidenced by the fact that once these results came out, All of those folks who were not there in the market— who were in the command-and-control group— clamored to be included, to join the market.

And you would recall the Acid Rain Program from the U.S. I mean, that had a benefits-to-cost ratio of about 50-something to one. This city of 16 million— with this reduction in emissions, this improvement in compliance cost, this cost of whatever treatment plants, treatment systems that they needed to put in— this cost-benefit ratio is well over 200.

So it’s— I mean, you can imagine the impact that this is having. And all of this took place without a single new dollar or rupee being spent by the Pollution Control Board. So no increase in regulatory capacity.

Arvid Viaene: So let’s hear his main take-away of this experiment in Surat:

Kaushik Deb: So what this experiment really kind of does prove is that, classically, we always think that market-based solutions are so complex, so complicated— how do regulatory environments with limited regulatory capacity deliver these really complicated solutions? What this market— what this experiment— proves is that these are the right tools to be used with limited regulatory capacity.

And these are the right tools that ensure that, with limited regulatory capacity, you can achieve the kind of emission performance that you want with lower costs. And lower costs, if you kind of think this through, are essentially an opportunity for industry to grow.

Arvid Viaene: Kaushik is also implementing this vision. Because setting up a new cap-and-trade market takes a lot of effort and learning by doing. But now they are taking the lessons from Surat and using it to implement it in other states.

Kaushik Debb: So Gujarat was an exercise that Michael Greenstone and his colleagues started way back in 2008–09. And if I add up every year that went into getting Gujarat up and running, I can easily think that this was an exercise that took about 10 to 15 years.

And this exercise took that long because this had never been done before, and every problem as it came up had to be solved. And this ranged from finding the right legal language for the regulation to identifying which emission-monitoring devices will meet these standards, their installation and calibration protocols, vendors who’d make this available, who would be the auditors for this, who would set up the trading platform, the data quality control and quality-assurance protocols— everything that came in there.

But having done all of that, we are hoping that the second market that we are going to set up now in the state of Maharashtra in India is something that we are able to do in a period of a year and a half or so. So from 15 years to 18 months is quite a steep improvement. And that’s the kind of learning curve that’s central to my ambition at EPIC. We talked about this briefly earlier. This is the kind of improvement in solar energy generation costs or wind energy generation costs that we’ve seen over the last 15 years.

We are in the process of launching this as a formal initiative— a joint initiative of J-PAL and EPIC— during the New York Climate Week, and we’ve christened this as the Emissions Market Accelerator.

Arvid Viaene: The Emissions Market Accelator has now been launched. And you can more information in the show notes. But the story continues. Let’s end on the following exciting developments that are happening in the broader cap-and-trade markets:

Kaushik Deb: So there’s— I mean, so this growth and this expansion that’s happening is both intensive and extensive. And let me draw that distinction. Once this experiment in Surat took off and delivered these results, now the default of the Gujarat Pollution Control Board for every pollution problem is markets.

So we are in the process of designing ETS schemes for— markets— industrial effluents for them for two central effluent treatment plants. So water pollution is being dealt with using these markets. They want to explore the use of markets for SO₂ as well. And we have a memorandum of understanding with them to think and start developing a carbon market for that state as well. So there is a lot of diffusion of the idea that markets can solve environmental problems across the board within that one state. But having seen that success, Maharashtra— the neighboring state— the SO₂ market that I talked about is well underway to use this as a tool and a solution to deal with their industrial-emissions problems as well.

We’ve just signed a memorandum of understanding with another neighboring state of Gujarat, Rajasthan, to set up an SO₂ market for them. This was signed at the last World Environment Day earlier this year.

And initial conversations with some other states in India are also happening. But if I were to put all of these three states together— if this was one big SO₂ trading program— this would be probably the world’s largest cap-and-trade scheme, much bigger than the EU ETS just in terms of population.

This would really be a hugely important and successful result. And seeing this now, there are conversations that we are having with numerous other countries and numerous other geographies and jurisdictions around the world on trying to use cap-and-trade schemes as solutions to deal with all sorts of environmental problems, including carbon markets.

There has been a trend recently— I would say a slightly aggressive trend— in the sense of a move away from climate regulation and climate management, especially using economic instruments.

But I think once some of these experiments and some of these markets become a lot more viable and grow, it will become a much more widespread tool. At this point, everyone in our community, in the environmental community, kind of thinks that cap-and-trade schemes are sophisticated and useful only in very developed jurisdictions like Europe and, in a pre-current-administration world, the U.S.. But what we are doing is showing that this is a tool that’s much more widely applicable in the developing world.

Arvid Viaene: Today’s best-of documented one problem across two countries and two policy designs. China used a command-and-control framework with explicit incentives for local officials and delivered large, rapid reductions. India used a decentralized approach where states could implement cap-and-trade for particulates, achieving near-universal compliance and substantial emissions cuts at lower cost—then expanding to other pollutants and jurisdictions. The common denominator is measurement: transparent data supported enforcement in China and enabled market design in India. In the show notes, I’ve linked to the underlying studies and programs discussed. Next time, we’ll run a best-of on CO₂ and climate.

Introduction

In this interview, I talked with Marion Kruger, co-founder of Remove. He explains how carbon removal technologies are essential for achieving net zero targets by compensating for emissions that are impossible or extremely expensive to eliminate. Carbon removal is what puts the “net” in net zero, and by 2050, we’ll need to remove 5-10 gigatons of CO2 annually—creating an industry comparable in size to today’s oil and gas sector.
He also has a new book out called “Race to Zero, How Companies Can Lead the Way to Climate Neutrality” , which I highly recommend.

Topics of our conversation:

• Why carbon capture puts the “Net” in “Net-Zero”
• Three main types of carbon removal technologies: nature-based, hybrid, and engineered solutions
• Nature-based solutions like afforestation cost around $50/ton but face durability challenges
• Hybrid solutions like biochar offer middle-ground approaches at roughly $150/ton
• Engineered solutions like direct air capture provide the most permanent storage but currently cost $1000+/ton
• The “like-for-like principle” matches emission types with appropriate removal technologies
• Market development requires policy support, particularly integration into compliance systems like the EU ETS
• Geographic flexibility is needed to deploy removal solutions where they’re most cost-effective
• Carbon removal startups face a “valley of death” in financing that threatens industry development
• Public procurement programs and early innovation funding are critical to bridge the gap until markets mature
• Carbon removal complements rather than replaces emissions reduction efforts

For questions, comments or suggestions, you can contact me at arvid.viaene.ce@gmail.com

Transcript

Arvid Viaene: So first of all, today with me, I have a really special guest, which is Marian Krüger. He’s the co-founder and director of Remove, an organisation that supports European, Indian and African carbon removal startups. Previously, he headed the sustainability in business lab at ETH Zurich, advised industrial companies and public institutions on decarbonization and founded a successful solar startup. So Marian, welcome to the podcast.

Marian Krüger: Thanks for having me. Excited for the conversation.

Arvid Viaene: So I should mention, I had the pleasure recently of interviewing Ben Probst, a person who also works at ETH Zurich on carbon offsets. And it was an amazing interview, that was episode four. And in that episode we discussed carbon offsets. And because of that, I learned about you because you two have written a book together called Race to Zero, how companies can lead the way to climate neutrality. And I can really recommend the book. I learned a lot. And in it, you discuss carbon removal technologies at depth. And it’s something I didn’t know nothing about. And of course, I recommend people go check out the book.

Carbon Capture is What Put’s the Net in Net-Zero

Arvid Viaene: But today I’m really excited to talk about that topic with you. And I was wondering, just to start off with like, maybe a takeaway for people who don’t know about this, what would be one or what would be one or two things you would want them to take away about carbon removal technologies?

Marian Krüger: Yeah, I think at the highest level, we are all talking about net zero. Companies make net-zero goals. We as a globe, a global society, need to reach net zero. What puts the net in net zero? That is carbon removal. Otherwise, we would be talking about absolute zero, right? So if there’s one thing that listeners want to take away, carbon removal is what puts the net in that zero. What that implies is that we have some subtraction and addition of emissions at some point. As much as we want to try to avoid emissions and reduce them, there will be some emissions that we cannot eliminate or that are extremely expensive to eliminate. And for these emissions to compensate for these, so that at a net level, we have zero emissions or even negative emissions, that is what carbon removal does. It takes carbon out of the atmosphere that’s already there and stores it away for as long as possible.

And this is no small feat. If we look at the IPCC scenarios, we actually need a lot of it: we need between five and 10 gigatons. Just to put that in perspective, if we say five to 10 gigatons, that is maybe between 5 to 10% of the emissions. And if you say, let’s assume 100 US dollars per ton, we can talk prices or whether those are realistic later, that is, from an economic perspective about the size of today’s oil and gas industry.

Arvid Viaene: That’s about the size of the oil and gas industry. Could you elaborate on that?

Marian Krüger: So if we think about per year 2050, in twenty fifty, of course, all the way leading up to that, also after that, we need to remove five to 10 gigatons, so that’s billion tons of CO2 from the atmosphere. And if we assume every ton costs us about 100 US dollars to remove, that puts us from a revenue perspective or economic value perspective in the same ballpark of revenue of the current oil gas industry. So, at the highest level, I’m putting it very bluntly, we are building the reversal of the oil and gas industry. And that is no small feat, of course.

An overview of the three types of Cabon Capture Technologies

Arvid Viaene: Of course. Well, thanks for that. And I will even say that this topic is so fascinating that we already had a challenge in our first conversation, like, how do I approach this? Where do we start? Could you just then give a broad overview of the different types of technologies? Because I think people might not be aware of the full range here.

Marian Krüger: Yeah, absolutely. So there are a multitude of ways to take carbon of the atmosphere, right? And I think the first one that a lot of people think about, also often you see in the comments on LinkedIn or on their articles is, well, we already have the best solution. It’s trees, right? Why should we do anything else?

And trees here stand for a range of solutions that just rely on the best mechanism that it essentially nature has developed for this, photothensis. So during the growth of plants, these plants take up CO2 from the atmosphere and store it in their trunks, in their roots, in their biomass, right? And a lot of these solutions, such as afforestation, growing new trees, planting new trees, and mangrove restoration, increasing the soil stock in agricultural fields, all these solutions are subsumed as nature-based solutions. I don’t necessarily like the term, but that is one way to classify them. So it’s the first bucket. They are typically rather easy to implement, also at scale.

The problem is this carbon is not stored as durably as you want to. Why? Imagine a forest. Imagine a forest in the Amazon. And then imagine all the dangers that this forest is under, especially as the impacts of climate change increase, wildfires, deforestation, right? And as soon as there’s a fire, the carbon is re-emitted. So that is the reality for a lot of these nature-based solutions. We should be doing them for a lot of reasons, including carbon storage, but also because they’re great for ecosystems.

The second category, if you will, are what we also in our book called hybrid solutions. They take processes that nature already has in place to take carbon out of the atmosphere in one way or another, enhance them, or make them work better, more efficiently, and quicker. An example that some listeners may have heard about is biochar. You take biomass that a lot of the times doesn’t have any other use.

You put it in a oven called a pyrolyzer where you heat it up at high temperatures without the presence of oxygen. And that creates this charcoal at the end. Essentially, it looks very much like the charcoal you would be using for a barbecue. And that stores the carbon quite permanently. And then it could be used as fertilizer, for instance, on agriculture fields. So that’s an example where the carbon storage has happened through nature. We’re still using biomass, but we’re enhancing it. That’s the second category, just to give you one feeling. There are a lot of other options in this category as well.

And in the third one is what we really call engineered solutions. So here we’re really relying on technology to do the job for us. One of them would be direct air capture. As the name suggests, we have a technology that takes air out of the atmosphere, strips the carbon away, then at the end of this machine, you can imagine like a big fan, the air out the air comes out without CO2. And the CO2 we then, for instance, store underground in empty gas fields.

So that’s at the highest level an idea about what the options we have at our disposal in card removal. And within each, there’s a market of diverse options to use them and to develop these.

Arvid Viaene: Yeah, thanks so much for that overview. So the first solution is nature, the second is the hybrid and three the engineered solutions. Because the first thing I would think of is like the direct air capture. Exactly like trees have a cycle, because of the conversation with Ben, are there differences in uncertainty in the measurement? For example, did you actually grow the trees you want to grow. It is easier to implement versus the engineering solutions I would imagine. But the engineering can be more credibly monitored in some sense, but they are more expensive. Is that the trade-off that we’re looking at?

Durability of Carbon Capture Technologies and the Like-for-Like Principle

Marian Krüger: I think so, yeah. At the highest level, I think that’s a distinction or a statement that you can make, right? And I think that’s also something to very important to take away with. Carbon removal is not created equal, right? It’s not one uniform thing. Actually there is a wide variety of things that depending on the method have certain benefits, certain qualities, certain advantages and certain disadvantages.

And what comes with that is different carbon removal methods and thus the credits that are being generated. So that’s essentially the verification that a ton of carbon removal has been taken out of the atmosphere. Ben has talked about this in the last episode with you.

They can be used for and should be used for different things. So there’s a thing, and this might already go in regulation and policy a bit. There’s a thing called the “like-for-like” principle. So if we think about reaching at zero, that’s what we want to do as a globe, right? We will have,

A variety of emissions at net zero, be that in 2040, be that in 2045, be that in 2050. We will continue to have some fossil emissions, say, for instance, from flying, right, or for some industrial processes. They are just very, very hard to get rid of. These fossil emissions will stay in the atmosphere for extended periods of time. So the like-for-like principle then suggests we need to take carbon out of the atmosphere for an equally long amount of time.

For these, for instance, a direct air capture credit would be good, there we can credibly monitor and make sure that ton of CO2 we have taken out of the atmosphere is going to stay away from the atmosphere for millennia. There are other ways to do this as well. Enhanced weathering, for instance, would be another one. Now, we will also have some emissions from agriculture, such as Nitrous oxide and methane. So these are short-lived emissions that do not are not as long in the atmosphere as a fossil emission. For these, we can think about the like-for-like principle, with more or less durable carbon removal solutions, such as afforestation, and solid carbon regeneration. So there’s not just a difference in the solutions, there’s also a difference in what we do with the solutions to compensate in the end.

Arvid Viaene: If I recap that it’s whenever CO2 is emitted in the atmosphere, it’s there for a very long time. So you need a very long, almost permanent solution. Whereas for methane, they’re just there like much shorter. So you can actually look at these shorter cycles because you capture it, the methane goes away and then if you remove the forest, then it just balances out.

Marian Krüger: Exactly, exactly. It’s obviously not as easy as that because methane is very potent. So there are there’s factors that you need to assume and there are very smart people working on how to best do this. But at the highest level, think of like-for-like. Long emissions, long fossil emissions need long permanent carbon removal. Short-term emissions can also do with others.

Arvid Viaene: Just as a side question, but in your book, you said you focus mostly on CO2. Has there been research on methane, too, to remove it? Like to remove some methane from the atmosphere? Because it’s as you say, methane and nitrous oxide are very potent. Is there something happening on that front?

Marian Krüger: There is a bit of work happening, luckily. If we think of where carbon removal is right now, the work on super pollutants is probably five, six, seven a years behind. I think the main takeaway from the super pollutants is that our main job there is to reduce and to avoid them reaching the atmosphere in the first place. And especially with methane, there are so many methane leaks from pipelines, for instance. And then, of course, there’s enteric methane emissions from livestock. These are the big, big emitters that we should be thinking about.

For removal, we’ve seen the occasional methane removal startup that has applied to our program. Particularly, it’s really very, very early days. And if we think the carbon removal policy landscape is in its infancy, let’s not even go talk about super pollutants, right? Because they’re really there’s absolutely nothing.

Cost ranges for the different Carbon-capture Technologies

Arvid Viaene: Okay. Sounds good. Thanks for that, I was curious about that. And we’ll talk about the landscape in more detail. So then maybe as a bridge from that, the podcast is called Climate Economics. So we have to talk some numbers about the cost per ton. So could you give us maybe some ranges of estimates of like how costly these types of solutions are to remove tons of CO2?

Marian Krüger: Yeah, sure. And you’ll realize also with the numbers that I’ll be giving you that the range is massive, right? And I think this, again, reflects the diversity of carbon removal methods that we have, both in how mature they are, how much they’ve been deployed, whether at scale or really in their infancy, with the potential of cost reductions that are still ahead. I think one parameter that we need to take into account again, and it will come up again, is this durability or permanence of carbon storage. Because that really differentiates one carbon removal solution from the other, and thus also is and bit of a proxy for the price.

So if we start with the nature-based solutions, right? There you can get high quality nature restoration so credits. So a ton of carbon removed through soil carbon sequestration or afforestation for 50 US dollars, for instance.

Now it depends on the contract, but those then maybe have a durability of 20 years, 30 years, 40 years, 50 years, but typically around that range. But that means if you have an emission today, typically 20, 30, 40 years down the road, if you want to continue to compensate for that, you need to buy another credit. So that is something to keep in mind here. Might be cheaper at first sight, but if you want to continuously compensate for the emission today, you would need to vertical stack and horizontal stack.

But there are ways that you need to deal with that. On the other end of that spectrum, a direct air capture credit easily, especially from the novel technologies, can cost you four digits, like a thousand US per ton. You could say, well, it’s the same tunnel that we take out of the atmosphere. What the difference is, is how sure are we that it will remain out of the atmosphere? And what’s the risk of reversal, right? In between, you have quite established solutions such as biochar, which I’ve mentioned, where you can get like a high quality, industrially created biochar credit for let’s say 150 US, right?

That is the smallest range, yes. And then you have some others, for instance, ocean capture solutions or enhanced weathering solutions, which are more than between, let’s say, $200 -$700, even also ranging to the thousands [of dollars]. And what’s interesting here is also if we look, think cost projections and where could this head? When I did this crude calculation of how much economic value this industry could have in 2050, at a 100 US.

This 100 US dollars is this ominous number that actually people have tried tracing it back and no one really exactly knows where it comes from. I don’t think that [The $100/ton] is the right target to have in mind because it’s quite unrealistic to get there. If we say we need carbon removal to come down to $100 US per ton. For a lot of the solutions, that’s just very, very hard, if not impossible. And on the other end, think what’s the basis for this, right? If we think social cost of carbon, it’s definitely higher than a hundred US dollars. Maybe a better proxy is what the marginal abatement costs are in hard to abate sectors. And at some point carbon removal will be cheaper than abating a ton at 250 US in the steel industry, for instance. That of course is not as nice of a number as to say we need to go down to 100, but probably more realistic. Because those are going to be the decisions being made on the corporate side of whether they need to buy carbon removal or whether they can reduce internally.

The Importance of Policy driven-demand for Carbon Capture Start-ups

Arvid Viaene: Yeah, then we also exact get into policy because, for example, in the ede EU with the EU ETS, they also have the option to buy it, so to say, from a different company. Because, if we have a future where the caps just get tighter and tighter, which they would have to, , given the goals, the prices would start to rise. And then you, like, if you say, like, the biochar was like 150 dollars. So how long is biochar?

Marian Krüger: It depends on how it’s produced. But there is high-quality biochar. There’s still research ongoing. It’s a bit of a debate. But the most recent science indicates that it can be permanent for up to a thousand years.

Arvid Viaene: Okay so pretty much infinity for any discount rate. Because that would be from an economic perspective, if you’ve got an EU ETS, and you’ve got some established technology for a thousand years, then that’s like an upper cap on the EU ETS. If it were to be like credibly integrated. I think that to me is another very promising thing, as these prices were to go up, at some point you could hit it if it’s well integrated.

Marian Krüger: Indeed, yeah. And that’s that’s why lot of work and also to be fair, hope is being placed into ETS integration, whatever that integration may look like. I think there is, again, smart people working on it. There are a variety of ways that this could happen there’s no way we will reach the five to 10 gigatons if this remains a voluntary market as it is right now. There’s just absolutely no way right now. Now we rely on a selected number of companies that can afford to buy carbon removal at these high prices because they have made public net zero claims and pledges and want to one to live up to them. But in essence, this is voluntary. And if push comes to shove, and we have seen this with a bit of an economic downturn, that tides have shifted a bit.

Marian Krüger: And the startups that we work with, they see this day in and day out. In a very crude analogy, right now, carbon removal is a vitamin. And unless it becomes a painkiller, we will have a very, very hard time ramping up supply. And the ETS is one main, if not the main way that we can really get to scale.

Arvid Viaene: There are a few follow-up questions I have for that. One is that the current regime in the US isn’t the most favourable for these types of things, but that might change with the next president. But the research needs to keep happening. I feel in the book, I also got the sense that if there’s not enough demand, well, then the startups will fail because they need their funding, they need their promise. There have been some companies that’ve done individual purchases, but they need to get there. I think in the book, you also talk about there being funding for the initial research. But then scaling it up is intensive. So in these times of lower demand and more uncertainty, I can imagine it’s very hard to keep the research going to get it down to these more affordable numbers. I think that just seems like a big challenge.

Marian Krüger: Absolutely. You hit the nail on the head. This is essentially the work that we do day in and day out supporting these startups, right? Is not really helping them scale right now. Right now, it’s about helping them to survive.

Right now, there’s not enough demand. The problem with that is it’s not only that there’s not enough revenue coming in, but the volumes that they will be selling are not enough to really hold them afloat anyway. But what that means is that investors stay on the sidelines because they perceive the market risk to be too high. And without investment, you cannot continue to develop your technology, come down the cost curve, and become more attractive for demand down the line. So it’s a bit of a vicious circle, actually.

So that’s why, well, there’s a variety of ways that you can alleviate this a bit. One needs to come from the policy side. And indeed, what we have seen in the US is they, in the Biden administration, under the Biden administration, started out with significant incentive schemes for carbon removal startups, so albeit a bit focused on some technologies, still, that was strong and great.

And now some, luckily not all, some have been pulled back. And we see the immediate effects of that. Luckily, individual member countries in the EU and the EU in itself seem to be moving to jump in and take that position a bit. We still need to see the actual results of this, but there are promising signs which need to happen. Otherwise the problem is, that I won’t get tired of being on stage and saying this, we cannot afford to lose just this generation of carbon removal startups. Because if we need to start from zero in 2030, 2031, when from one day to the next EU ETS integration comes, we won’t just be there with millions of tons of core removal. This generation is the one that will be delivering those removals in 2030, 2031.

Arvid Viaene: So then we’re bouncing all over the place, which I love. Is it so I always have like these so many questions. How do you maybe see the integration, the EU ETS?

If maybe if it’s, let me start it again. How From what you’re you’re saying, it sounds that the potential integration in the EETS might be a credible sign. Also to investors, if you can get connection to this scheme in a credible way, that’s like, if your future revenues are more guaranteed rather than these one-offs, I think any even when you report the tailwinds of policy versus the which I loved.

Arvid Viaene: How is that going? Is there some sign there or like what is happening there?

Marian Krüger: I completely agree, I think. So the earliest that the integration would be happening and in operation is 2030, 2031. That’s of course, in especially startup land, that’s an eternity, right? But what would already happen massively if there was the integration on the horizon? Because if we knew that happened if we knew that market existed, investors, as well as the companies that are compliant under the or need to be compliant under the ETS, we need to start moving.

Because if I’m a cement company and I’m regulated by the ETS, if I start looking at this in 2029, it’s too late. I need to establish internal capacity. I need to establish relationships to suppliers now rather than in 2029. Same with investors. If I know that market will be there, I’m very happy to take up the market risk until that time. That is and essentially what venture capital is for, to take up that risk and to make those bets. By summer 2026 is when the Commission needs to come up with a proposal for the Parliament and the Council to how negative emissions, so carbon removal, are going to be integrated into the ETS. So everyone is looking, waiting for that.

There’s good people working on the policy side, like Carbon Gap and other organizations to argue and inform about the need and how to do this in the best way. We are seeing on the UK side, for instance, which has just come out with a strong statement from the government to say, yes, carbon removal and their lingwoods called greenhouse gas removal is going to be integrated come 2028. We already have some integration in the Japanese ETS. So there’s some good signs. But of course, the big one is the European ETS because it’s by far the biggest compliance regime in the world.

Competitiveness of carbon capture in a cap-and-trade scheme

Arvid Viaene: And then how do you see it for like the direct air capture? Because I think you said there, maybe it will come down to 250 dollars per ton. It’d be hard to get it lower. At that point, it would still be more or less something voluntary by firms to do. But at least then you could get it into the market. Because at the price it would be trading, say it goes 100, 150, it still wouldn’t be competitive, so to say, in the market unless it really goes high.

Marian Krüger: Yeah, I think that’s a very good question in terms of how this play will play out. I think it’s going to be obviously a question of how much to supply will there be of other carbon removal all carbon removal is essentially limited by one or another parameter or input, right?

Marian Krüger: If we talk biochar, it’s great that we can do it at 150 today. Biomass at some point will be limited because also there’s other use cases for that biomass. Think bioplastics, right, which also helps us mitigate. On the direct air capture side, for instance, there’s only so much. It’s quite energy intensive. So we need to think about whether there is enough energy. Do we need to put extra energy on the grid? There are land use problems with some of the other solutions. So in the end, we will have a mixed bag of carbon removal. At various point price points. It’s going to be very interesting to see how direct agriculture fits into something like the EU ETS. Maybe just going to be a limited supply of biochar in the EUTS at some point, once that is used up, more higher-priced removals will come in to remain compliant.

It’s also going to be very interesting to see how far their architecture companies can get their prices down, right? Obviously, because there’s this ominous goal, if you look in investor presentations, they’ll tell you they can come down to 100. Well, if you give me an Excel, I can model everything to come down to 100. I understand that right? With certain assumptions, you can do that. I think that’s also a very interesting thing to think about, how do we think about cost curves and scaling down, right? Again, carbon removal is very, very diverse and we cannot assume learning rates across the board. They’re going to be different. I think for some solutions where CapEx dominates, then massive cost reductions are possible, right?

We’re going to be building better, cheaper and bigger. And there we can massively come down. If OPEX dominates energy demand, of course, we can come down, but there’s going to be limits to that. So I think we cannot be, luckily, know, the startups that we work with, they are not blind and just assume solar type of cost reductions or battery type of cost reductions for all of carbon removal. That’s just not going to be realistic.

International Dimension of Carbon Removal

Arvid Viaene: Yeah, because that’s like the interesting tension that you’ve mentioned this in your book, that energy is cheaper in the US. So it’s actually cheaper to do some of these things in the US than in the EU where energy prices are just higher. So in some sense, you would want them to develop in the US, bring down the costs and then we can do them in the EU, which is why the Biden incentives probably were so helpful. Because then you get the low energy, which is one of the main focus points with the current administration. Like we want to keep energy prices low, versus Europe when then they’re just higher.

Marian Krüger: I think you’re hitting on a very interesting point. What’s special about carbon removal is that wherever this is produced doesn’t matter. The atmosphere doesn’t care. Of course, the economic value resides wherever the carbon removal solution is supplied, but the benefits is for all of us. So if we think about where which carbon removal method is going to be deployed, there is going to be there are going to be geographies where a certain carbon removal solution is optimal where others are not. Now, how does this pan out with the EU, for instance, saying in their carbon removal, carbon farming framework, which is going to be the guardrails of what makes up carbon removal. Credits need to be generated in the EU, on EU soil.

I don’t know how credibly we can get to the volumes that we need to at prices that we need them to come if we restrict ourselves to say biochar credit. And say a high-quality biochar credit cannot come from the global south. GHowever, in the global South, it would be significantly cheaper, would have more co-benefits, and make more sense. That is going to be a very, very interesting thing to see how that pans out because there are so many varying parameters and interests coming into it. Like in the US, as you say, energy prices are likely going to be cheaper. Access to storage likely is going to be cheaper. So, shouldn’t we deploy more DAC in the US or in the EMEA region as opposed to putting it in land-constrained and energy-constrained Europe?

Arvid Viaene: Yeah, because then it’s generally like, oh, we also want to stimulate jobs and all these other concerns. But it’s like you say, from a cost effectiveness global perspective, it doesn’t need to be in Europe. Now, of course, there’s probably some lobbying there. And then because they say Europe were constrained on the landmass compared to other places. And would you recommend some more flexibility on that front?

Because then I think there’s there’s two counters that I would think of. It’s like, well, one is you want to stimulate the economy, and the general politician’s concern. The other concern, because I asked some friends also for feedback, is that, well, will it be credible? If you go to the global south and monitoring gets trickier, Now, the EU is already talking about carbon offsets. So, in some sense, they can also do a part of this, which can be abroad. This doesn’t have to be a 100-0 thing.

Importance of an International Carbon Capture Approach

Arvid Viaene: But I think that the credibility comes up then. We talked this with Ben, but like, how is it in terms of the verification of these things?

Marian Krüger: Very good point I think we have the cautionary tale of CDM credits in the past what they did to compliance regimes so that’s something that I think is informing the cautionary nature or approach stance on the EU side. I do not see a scenario where we can hit the volumes we need if EU wants to remain competitive. And that is one of the main goals of the current commission, right? Competitiveness. And that competitiveness for me includes remaining competitive in light of increasing climate regulation around the globe and staying true to the climate commitments that you have made. Then the ETS needs to be able to sustain ambition while maintaining competitiveness at volumes that I don’t see coming purely out of Europe. Probably in the ramp up, that is not going to be a problem, but we are just constrained in really almost all carbon removal methods. I don’t think that, don’t know whether that study or research has been done to actually model this of whether we could deliver all the removals we would need in Europe, from Europe. That would be very interesting paper to do. I’d love to see that.

Arvid Viaene: Yeah, to all the researchers listening in. Because like you said, there’s probably physical constraints, like the biomass, the things, you’ve got to store it, which we haven’t talked about much.

Marian Krüger: And then again, from a CDR, global CDR perspective, cost effectiveness, it makes so much more sense to deploy some of these solutions outside of the EU, right? For a variety of reasons, one of them being cost. That’s why we’re also very active in the global South, in India and Africa or soon in Latin America. There’s just so much potential for carbon removal that is untapped in regions, that by the way are being hit the hardest by climate change and have had the least to do with it. So this also allows these regions to take up a position that is more than adaptation, but actually a more active role in mitigation.

Arvid Viaene: I think it’s a very good point. How is that going? Because in your startup, you mentioned, or I saw online, you focused on Europe, India, and Africa. Is it suddenly growing there? Because often, they’re doing a podcast like that, which is coming out very soon, about air pollution in India. Like, that’s where the main focus is because it’s just so costly in terms of current lives lost. So I was surprised. There also seems to be a growing trend there to already focus on these carbon removal options or not.

Marian Krüger: Yeah, it’s a good point also that you mentioned air pollution. The carbon removal narrative is a very different one in a place like India or sub-Saharan Africa than it is in Europe. Europe has demand. India has zero demand for carbon removal. They have other things to think about. That is reflected in their net zero goal by 2070.

They have immediate issues on air pollution, health concerns, economic resilience, food security. So the narrative there really is what we in Europe consider co-benefits of certain carbon removal solutions. [For those areas], those are actually the main benefits and carbon comes as a secondary consideration. Right, which to one end is good because it facilitates deployment, also at scale, in these geographies. And sometimes it even generates other revenue streams.

If, for instance, you can sell biochar as fertilizer, it reduces your reliance on carbon removal revenues from the voluntary carbon markets. At the other end, the challenge for startups in the global south is, how do I find a buyer for my credits? And that is, one of the main reasons why we entered those regions. By the way, we always work with local partners, we don’t think we understand India or Sub-Saharan Africa. Quite the contrary, but that’s why we have local partners. But because there’s so much potential for the deployment of these removal solutions, not only for carbon reasons, but also for other reasons. But carbon revenue will always need to play a role in these business models. And it’s just a big struggle for them to access the market. And you asked why we did that and how it’s going. Well, that really is our main task there to help them connect to the global carbon removal ecosystem. Because these entrepreneurs, they’re doing a hell of a job in ecosystems that are very immature and nascent.

Arvid Viaene: Maybe one thing that I was wondering about. So we’ve talked about the integration, the EU ETS. If you were to be, if you were to have like a budget of like two to 5 million a year, how would you best use it to support the industry or the development?

Marian Krüger: Probably three things. And we’ve talked about the importance of demand, right? There’s no way we can scale this industry without demand. And in the absence of there being compliance demand, I think it would be up on either philanthropy or governments to come in to provide these demand signals. So one thing would be to do a public procurement program or philanthropic procurement program at significant size, right? To just stimulate the market, to allow companies to show the traction vis-a-vis investors. And then certainly you’re in a virtuous cycle, not in a vicious cycle. And think this, so that’s more on the demand side.

I think the other two options that I would do are on the supply side. One is early innovation grants in the EU. We have the EU Innovation Fund, which is great, but which tackles projects that are 100 million plus. Barely any carbon removal project is at that level. So it would need to have a lot earlier stage support because while there are already quite number of car removal methods out there and startups out there. And we have 160 have gone through our program, right?

Marian Krüger: And there are so many more. I do believe that potentially the most relevant and most efficient car removal methods are yet to be discovered. So I do not think right now is the moment to just say, okay, we don’t need to invest into early R&D, into early innovation anymore. I think quite the contrary, let’s double down on that.

The second one would be the generation that has now evolved over the last couple of years, a lot of them are now at a point where, because of the problems on the economic side, they struggle to finance their first projects. They are not in a stage yet where they can go to a bank and just say, I need a loan. But financing everything through equity from investors would be way too expensive and equity investors are also on the sidelines. So there’s this valley of death for all these startups where, again, public or philanthropic money could come in say, hey, we are willing to take a bit of a higher risk in a, say, loan guarantee program. Which in my mind would have a massively positive effect on the current generation, the current cohort of startups, to bring them, to allow them to leapfrog survive until say 2028, 2029, 2030. And with two to 5 million billion, I could do a lot. So I wouldn’t mind have that cash lying around.

Arvid Viaene: Yeah, I was actually saying, yeah, because even maybe the even amount is too high, it’s almost if the 2026 commission decides like even to say 500 million guaranteed even just for the EU guaranteed things or for things that have some hyper verified things. Because, that, based on what I get, that would be massive because it’s like there’s some things that are happening. It’s just the market just isn’t there. And especially now, with the recent development..

Marian Krüger: Absolutely. I think it’s, and this would have two elements of this. One, of course, the cache itself, but also the signal. But The U.S. In the last months or half year of the Biden administration, they announced a public procurement program. It was 35 million. So it’s nothing. Right. It’s nothing. But the signal it sent was what mattered.

Arvid Viaene: Exactly. Because that’s what the Venture capitalists are also probably looking at. Like, are these procurements, is there anything happening?

Arvid Viaene: Because I think sometimes the revenue of the EU ETS is now earmarked for green developments, like the social just transition. Like Governments cannot spend on anything, like it has to be related to climate. But I saw some things that’s often used for innovation projects for houses and then like electric cars.

Arvid Viaene: But if you look at the emissions that are the abatement costs for like electric cars versus so gasoline, they’re also not always the highest. So in some sense, I’m just, I’m really brainstorming here. I never had this thought, but like, if you could just earmark 2% of the EU ETS revenue in terms of like guaranteed commitment for carbon removal projects, Like you say, you probably don’t need much, just a guaranteed size thing. And then now of course the direct air capture still would probably be the least competitive. Like it would still probably be first like biochar, some, some of these other things first, but at least you’re already like starting up the, the, the process.

Marian Krüger: Absolutely. And then it depends also on the mandate that you have. Is the mandate to buy the highest volume at the lowest price, given a certain standard, or is the mandate to really buy and develop the market? The market as we have it right now wouldn’t exist if it wasn’t for some big tech companies in the US who essentially said, okay, we in the future will rely on this market. And in order for it to exist, we will take up this catalytic role. In the book, we write about this advanced market commitment that it’s called Frontier it’s a combination of, think, , McKinsey, Metastripe, all of these companies come together and said, we will rely on this market, so let’s make sure it exists.

Marian Krüger: So they buy catalytically and they buy at prices that economically don’t make any sense. They buy at a direct-to-capture credit at 1,500 right? Right. But why do they buy? Because they know without this, we will never get to cost that 2030 and 2035. When their pledges they to rely on it.

Marian Krüger (cont.): And their pledges it they need to rely on

Arvid Viaene: Great. Is there anything we haven’t talked about or that you wish I could have asked you, you’re like, oh this would still be good to know for the people listening?

Marian Krüger: I think we covered really a lot, to be honest. I think the main messages that are relevant for me, I got across. It was very good that you started out with the front loading.

Arvid Viaene: Sounds good, maybe as a final question, what about mitigation deterrence?

Marian Krüger: Yeah, I think that’s a question or concern that many people have asked. So mitigation returns essentially means that because we have carbon removal, does that mean we do less on the reduction and avoidance side? And I think it would be blind to say mitigation returns doesn’t exist or the risk doesn’t exist. It does exist. Right, we have carbon removal as a solution that can stand in for the avoidance of reduction. I think there are several ways that we can mitigate that risk, though. One is, if we have targets, that ideally, those should be separate targets. So should we start to have an avoidance reduction target and we should have a removal target. By that nature, we already distinguish between the two and don’t allow for a combination or a mingling of them.

Then I mentioned earlier the like-for-like principle, also a way to strengthen this. And what is connected to like-for-like is of the higher prices for fossil emissions and removals that can compensate for them, carbon removal will often not be the cheapest option. If we go the marginal abatement curve, if we go it up, there’s probably a large chunk of emissions that are a lot cheaper to abate than to use high quality, durable carbon removal. Only at some point, there will be an inflexion point. And at this inflection point, that is where potential mitigation turns can come in.

Now, then the argument is, well, maybe carbon removal is the Better quote unquote or at least economically better option because it’s cheaper to use that than to mitigate other ways. There are, for instance, with sustainable aviation fuel, some analyses suggest that maybe using fossil jet fuel carbon removal is economically, it does make more sense economically than to use. Now, there are other reasons why you might not want to do that, it prolongs the use of fossil fuels and creates a lock-in effect with legacy fossil players. So I totally buy those arguments. But solely from a economic perspective, there are arguments where carbon removal is the optimal solution rather than continuing to go down the avoidance reduction in marginal abatement curve.

Arvid Viaene: Awesome. Then I would say, Marian, thank you so much for your time today. It’s been really interesting. I think I also got away a lot in terms of like the landscape and, , maybe with the upcoming EU developments, we’ll have to talk again about then how we can how we can get this into the EU stuff. So But thanks so much for taking the time. I really appreciate it. And I think I got a lot of it. I’m sure people get a lot of it. So thank you so much.

Marian Krüger: Thanks for having me. This was fun.

Outline

1. Introduction

2. Transcript

1. Introduction

In this episode, I am joined by Professor Dr. Lorenzo Trimarchi to discuss his paper "The Unintended Consequences of Trade Protection on the Environment" in the Journal of Development Economics.

We discuss how how the 2018 US-China trade war triggered unexpected environmental consequences when Chinese officials relaxed pollution standards to

Topics with time-stamps:
* A puzzling observation: Pollution went up after the Trade War [1:28]
* 3 Measures of Environmental Stringency [6:33]
* Chinese Political Economy and Politician's Promotion Criteria [11:50]
* Trade-offs Between Growth and Environment [19:46]
* Younger politicians Were More Likely to Relax Environmental Standards [20:30]
* Weak Effects of Environmental Regulation on Economic Performance [24:30]
* The US-China Trade War Explained [28:30]
* The Story of the Targeted Retaliatory Tariffs from China [36:40]
* Chinese Policy Experimentation & A Positive Take-away [38:40
* Implications for EU Carbon Border Tax & Uniform Tariffs [41:30]
* Future Research on Climate Politics [46:08]

counter economic pressure from tariffs.

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2. Transcript

Introduction Interview

Arvid Viaene: So, hi and welcome to another episode of Climate Economics with me, your host, Arvid Viaene. And today I have the pleasure of talking to Professor Lorenzo Trimarchi , an economist who is doing exciting research at the intersection of trade and the environment. And he recently published a paper in the Journal of Development Economics, on the US-China trade war of 2018 called the “Unintended consequences of trade protection on the environment”. And he shows that a trade war can lead to negative consequences for the environment, and which we'll discuss extensively in this episode. And I think there's a lot to be learned from that paper, given that the current US administration has been quite active in not only threatening to raise tariffs but also executing on that threat.

So my guest is Lorenzo Trimarchi, who is an associate professor of economics at the University de Namur in Belgium. He holds a PhD in economics from the European Center for Advanced Research in Economics and Statistics of the Université Libre de Bruxelles. So in some ways, this is a hometown game because he's in Belgium. And his research interests are international trade, political economy, banking and corporate finance. So Lorenzo, welcome to the podcast.

Lorenzo Trimarchi: Thank you very much, Arvid. Thank you for inviting me. Sounds a fantastic project. I'm very happy to participate.

General Introduction to the Paper - Counter-intuitive: Air Pollution and CO2 Went Up following the Trade War

Arvid Viaene: Thank you very much. And as I said in the introduction, I'm very excited to talk to you because I think there's a lot to be learned from your paper. And so I was thinking to start off, could you just give us a general overview of your paper and what you were trying to do?

Lorenzo Trimarchi: Thank you, Arvid, for the invitation again. And this is a project that we started years ago, joined with Taipeng Li, Rui Xie, and Guohao Yang. And this is a project in at the intersection between international trade and environmental economics. And in this project, we try to understand what the impact is of the trade war on environmental regulation in China. But I want to tell you a bit about the story of the project, to help you understand how the project was born and what the reasoning was behind our research plan. So the project started in January 2021, Guahao started to work on a simpler research line with the Taipeng and Rui, in which they were just saying: there is a general literature on the impact of trade policy on the environment. And there is the famous paper of Grossman and Kruger about the cost of NAFTA for the environment.

So starting from this very standard international trade and environment question, Guahao, Taipeng and Rui were running regressions investigating the impact of the trade world on pollution. And this preliminary evidence and surprise was pointing at the trade world triggering an increase in pollution in China.

Why is that surprising? Because as a trade economist, we tend to think about tariff as mainly as a negative income shock, especially for developing countries. So we expect, okay, China is a country heavily specialized in the manufacturing. If we give a large trade shock, we expect China to reduce income and therefore to decrease pollution. And that's the prior my co-authors had at the beginning. And this was also supported from some preliminary evidence. So on the economic side, by Beijing Li and Devin Shore show in their QJE paper that the trade war was a negative economic shock for China.

So for us this was absolutely puzzling and we were trying to come up with different explanations of how this was possible, investigating all the three channels under which trade economists think about the relationship between trade and the environment, that is the scale effect, so the impact, this income effect that we say the tariff should have a negative impact on pollution because we decrease the scale of production.

So take the composition effect: maybe China, because tariffs are somehow disproportionately accounting for polluting the polluted products, China changed the product span and they produced more polluted products. And the third is the famous regulatory effect. And through discussion with my co-authors, we started to think this may be the channel, also because the general discussion around the world, if you remember the time, we are speaking about 2021, we are in the aftermath of COVID, after we had the Russian aggression to Ukraine, and we observed several reversals of historical events and environmental policies around the world. Iincluding if you think to Germany, we had this big case of a socialist and the Green Coalition that decided to open again coal plants in Germany and we started to think to this idea, maybe the government reacted to shape by changing regulation.

And together with my co-author, and I have to give especially credit to my co-author for this massive data collection on environmental regulation in China, we started to investigate if the trade war had an effect on environmental regulation.. And the answer is yes. This is the most robust part of our paper. So environmental regulation seems to be affected by the trade war in a way that the trade war induced an easing in environmental regulation for China. So this is the first big result. A negative shock in trade policy seems to have negative effect on environmental.

Arvid Viaene: So the first result is because there's tariffs, then the regulators make it easier for companies to comply or they lose lower the standards and that leads to the increase in pollution.

Lorenzo Trimarchi: Exactly, exactly. That's what we measure, because indeed that's the way we measure the change in environmental regulation. With my co-authors we collected three main measures. The first, if you want, is a more of political objective related measure, is by doing a machine learning technique, we went through all the prefectures, our analysis is at prefecture level, we went through all the prefectures annual reports, so those are official documents,

By the local Chinese Communist Party, in which the Chinese Communist Party explain their policy objective for the next year. So those are a very important. And we will discuss little about the Chinese political economy, but for the way the Chinese political economy works, those are important documents because

Arvid Viaene: Yeah, I can imagine.

Lorenzo Trimarchi: So this is the first source, so we tried to come up with an index of but environmental stringency of environmental policy. Of course, those are words, so we needed to collect the complementary information. And the first one, and this is a unique data set to the second one, we collected using something similar to the FOIA request, the Freedom of Information Act request that is in the United States. It’s something surprising, at least for me, but you have a similar type of mechanism in China in which a Chinese citizens can ask to the government, please, for research purposes, tell us what has been the policy in this area. And the fortunately enough, many prefectures answered to us

Arvid Viaene: I was surprised by that, and for those listeners in Europe, the Freedom of Information Act is something in the US as where you can ask for information from the government and they have to give it to you. So it’s interesting that there's something similar because it.

Lorenzo Trimarchi: There is something similar. Then I don't because I'm using the Freedom of Information Act for the US myself for another project, and I don't know if the level of compliance is comparable to what we have in Europe, in the United States.

But on our side, we were happy to see that there was cooperation by local government authorities that they were providing us clearly didn't get the coverage of 100% of the sample also because it is there is a manual data collection component because you need to physically write to all of them and clearly they need to reply to you.

Arvid Viaene: What was your sample then?

Lorenzo Trimarchi: Our sample, it changed by measure to measure. So for our main measure, that is the annual prefecture reports, is 290 prefectures from the 330. Because all the prefectures are assumed to release these annual reports. We have a period from 2013 to 2021.

Arvid Viaene: So this is a huge data set. And I think that's one of the amazing things is the data set, because it sounds you've just got most of China. Is that correct?

Lorenzo Trimarchi: Absolutely, this is most of China. , we might miss some more rural prefectures, some prefectures some mountain area. But if you see there is a map with with which we plot the data and the appendix, and there you can see that and fundamentally the region with most of the production are there. So we can fairly say we get at least a representative sample of the Chinese population and the Chinese production. That's what we care about. We want to capture where the economy is produced.

Arvid Viaene: Exactly. So you I think you had, you said you had three measures. So there's the text, there's this CO2 and PM2.5 of air pollution.

Lorenzo Trimarchi: Yes. And then we have a third one that are the environmental actions.

Arvid Viaene: Yeah.

Lorenzo Trimarchi: So this is a data set collected by the Beijing Law School and this dataset covers all sorts of penalty actions, all sorts of government fine intervention, fines against polluting firms. The third dataset must be interpreted with the caveat that if we show that the trade war induced a decline in penalty, you can interpret this as either less enforcement, either more compliance,

So since we cannot exclude the second, we use it as a robustness check because clearly we have a measurement problem there. But if you take the sum of the evidence, I think they all point in the same direction and this is quite reassuring, I think.

Arvid Viaene: Got it. So thanks for that. And then I we got deeper into the measurement, which I think you and your co-authors should give full credit for because the collection of data is tremendous. And because I think in you said you were going to get to the first part and then I interrupted you and then you were going to continue with this some second,

Lorenzo Trimarchi: Yeah, we saw this on emission and then we thought about regulation and then and then we found this effect on regulation.

Arvid Viaene: Then, I think it might be useful also for the listeners to understand more how the Chinese prefectures government works and what promotion criteria are. Because generally here, it's the major who gets elected in Europe and then there is some enforcement elections. So on this prefecture level, how does it work? And why were potentially politicians sensitive to relaxing environmental regulations, given the objective criteria that they had? So can you expand on that?

Lorenzo Trimarchi: Of course, of course. So one of I think of the cool part of the interesting part of this project, more interesting part of this project is to learn a lot about the Chinese political economy. Indeed, in our political system, in our democratic political system, mayors are appointed by electors. And the way they should establish politics, their policies,

It is by having some electoral platform upon which they are voted for. And the and for China, this is not just there, right? Because the the mayors or the local party secretary, they are appointed by higher level of their political power in China.

So, but I think that, I'm not the first to, we are not the first to study the Chinese political economy. There is a huge literature in the political economy to try to understand how bureaucracy and how political power is organized in China. And I think that the Chinese Communist Party was facing a big problem, especially in the aftermath of the collapse of the Soviet Union, the Chinese Communist Party changed a lot compared to the way it was organized in the 70s.

So clearly, they observed the collapse of the Soviet Union, and they observed that one of the reasons the Soviet Union collapsed was because there was a lack of incentives through the hierarchy.

And then the Chinese Communist Party started to think, how we can introduce incentives for performance within the party, And de facto, what I think is fascinating about the Chinese Communist Party is that more they are more organized like what we would consider a private corporation than a public administration board in Europe, because fundamentally they have these public officials that are more corporate executives with a performance contract. And they all compete in a tournament under which they will be selected for a higher level of power, based on some performance indicator established by the hierarchy. That can be the central hierarchy, it can be just a higher political hierarchy and geographical level, but it's really top-down. And in the 90s, the priority for the Chinese Communist Party was economic growth, as we know. So the Chinese Communist Party was very focused on growth.

Then in the 2000s, starting lady from 2008, we all remember with the Beijing Olympic Games, the pressure that the Chinese citizens were made on government to fight pollution. And in the 2010 year, we had this war on pollution declared by the Chinese government, and then environmental standards became more and more important for promotion.

So politicians care about career, and they know there are some objective indicators that will determine their career. And let's say that up to the trade war, both gdp and GDP growth and environmental goals, they were equally important.

Arvid Viaene: Thank you.

Lorenzo Trimarchi: That's what the previous papers established. I think what is important in our paper is that we say but now that the Chinese government for the first time probably since the 80s is facing a real economic shock, something changed and this shifted attention towards the economic goals versus environmental goals and because there is a trade-off between the two and maybe we want to talk about that later

Arvid Viaene: Exactly. So they are facing promotion criteria. I think it's actually a nice way to call it a tournament, they're competing with each other to get a promotion. They've got two goals, which is economic growth and then limiting air pollution. But then tariffs hit and there's a real economic shock and it seems that the person deciding the tournament is, now we're going to put it higher weight again on economic growth potentially.

Trade-offs between Economic growth and Air Pollution

Arvid Viaene: So, because then maybe can talk about why there's a tradeoff there, because it is not always recognized that there can a tradeoff between growth and and air pollution.

Lorenzo Trimarchi: Yes, another thing, for me this paper was super interesting. I learned a lot myself by working with my co-authors. I'm by region more of a political economy guy, and Guao is a trade and environment person, and Taipeng, we are very interested in the environment, so I had to learn a lot by myself as well. And one thing I was convinced of is that there is almost no trade-off between environmental regulation and productivity or efficiency. If we do green investment, this is good for productivity always. But it's actually not true because it depends from the nature of the firm. If you don't want to pollute, maybe you should make some investment in a technology that allow you to pollute less, and this can be costly for the firm, and especially in a period in which the margin might be less because you are under a trade war, this might be particularly important for a policymaker. You might want to relax environmental regulation. Not because you pollution per se, but because you want to somehow affect the cost function of the firm by decreasing the cost of production and hopefully be able still to be active on the export markets.

Arvid Viaene: Exactly. And I think that's, you even have this great quote in the beginning of your paper by literally a Chinese official saying, now that we have this trade war, we don't think, in order to keep growing at the same pace, we'll probably have to go back on some of of our environmental goals, which I think is was a very nice quote that I'm I'm going to put in the transcript in the show notes, because I think it's a very nice quote to illustrate this trade-off.

Because it's not only economic growth, I get the sense, it's also this more general social stability. And if firms were to shut down, that would also mean the loss of jobs. So it is also this social stability type of promotion criteria.

Lorenzo Trimarchi: Absolutely. This is, again, not a completely new idea. , this was is a beautiful book by the Nobel Prize of this year, so it's always a good moment to mention Daron Acemoglu and James Robinson. And there is a book about dictatorship. Democracy and dictatorship, which they speak, about the fact that all political systems, all political leaders, they want to survive a revolution, which they call revolution constraint.

And therefore, they care about stability. Eventually, in an autocratic system, this stability concern gets larger, but we can fairly say this is true for all political systems, also in Europe. Which one among us would think that the Green Party in Germany is against environmental goals? None of us. But still, under economic pressure, they open coal plants again. Or in Belgium, which I'm not following closely, but the Belgian politics, I perceive the attention towards environmental goal is declining towards the last years. And this is probably due to the fact that families are struggling, many families are struggling under the current economic condition. This is something we should think more about.

Arvid Viaene: I think in Europe, you see that the trade wars, now that there's extra tariffs and people get much worried about their jobs, the livelihood, firms shutting down and then, generally still environmental regulations are costly. So, there is some trade off there that you want to have. So you've done a lot of regression and robustness exercises, and this is, I take them at face value.

Why younger politicians might be more willing to relax environmental standards

Arvid Viaene: So, but one thing and I also observed is that you mentioned that some politicians, especially younger politicians might be more willing to make that trade-off of relaxing environmental regulations to promote some more competitiveness. Could you speak to that what was going on or why that might be the case?

Lorenzo Trimarchi: Absolutely. This is based again on the political economy of China. And still, when we think about an autocracy, we have to think about politicians as a person that, overall, fundamentally, faces a trade-off. A politician has a career concern; he wants to be promoted in the hierarchy, but they still care about their constituency. And I think environmental economics is a field in economics in which the welfare function is quite easy. We all benefit from a clean environment, and I think any politician in the world knows that for his or her own citizen having less pollution is a good thing for their welfare. So this is also the case in China. But the idea is that if you are younger, for instance, maybe for your career concerns are more important and you mightbe tempted to disregard more environmental regulations under pressure compared to GDP growth because you hope to be promoted.

And the same is for maybe a recently appointed mayor, but in reality, what we find as a super robust [result] is the role of patronage, which is also quite important in the Chinese political economy literature.

So what we find is when we all raise these three characteristics, what we find be the most relevant is being within the network of your provincial leader makes you more likely to implement this policy. And we are not sure in the paper, but we also collected the data on the provincial annual report work and we have seen that somehow there's been this shift also at the upper level. We have seen this at the provincial level, and very likely probably if you have a connection with the provincial leader, you want to please the your province leader because you think it will make more likely that somehow you will enter in the leadership of a province in future, you will have appointed to the Politburo, this type of partner that in our democratic.

Do we have this type of measure in our democratic system, this type of linkage in our democratic system? Yes, but they are less important, because in our system, what matters are votes, while in China what matters is being appointed. So this gives different incentives. Probably we can get same results, but we have different incentives.

Arvid Viaene: So if you have a clear link to the province or higher up, then you're more likely to make sure you meet the criteria. Then, someone who's less well-connected, maybe, their prospect for a career is maybe not as good. So they care maybe a little bit less about, meeting all the criteria. And it's as you say, this is one of the things I really learned about the paper is here, a mayor of a city it really is judged by the electorate directly on the trade-off. But there it's almost, you get judged by the people higher up in the hierarchy. So it is a bit like a company in that sense that there's performance criteria that you get judged on. And then there is a scorecard.

Relaxing of Chinese Environmental Standards Had a Surprisingly Weak Impact on Competitiveness

Arvid Viaene: So we've talked about, initially about that your co-authors and you had a different prior going into the research. Was there also so things that you found in the data along the way that surprised you?

Lorenzo Trimarchi: I think something that surprised me was the weak effect on the economic performance. Because, okay, there is a literature that says that regulation should affect productivity. And they changed the regulation. And somehow we hoped to find that this would change economic growth. But in reality, we don't find this large effect on the economic side. We find some effect for prefectures that eased environmental regulation a lot, then whether on the welfare point of view easing a lot, this shows you this entire saidures you that still a the Chinese Communist Party was facing trade-off and they were taking account trade-off, so not all prefector were easing environmentally we relaxing environmental by a lot, some did, for this few one we find some economic gains,

But for us, it was surprising to see that the gains were limited. So overall, if easing environmental regulation to counter-tariff might have seemed a good idea, I think what we learn that the effect was probably minimal. Or maybe the welfare costs are too high.

Arvid Viaene: So, there was a very observable effect on air pollution and CO2 emissions, but the impact on economic performance wasn't that big. Which in some sense would then make you think they score worse than their counterfactual counterpart who didn't relax the environmental regulations.

Lorenzo Trimarchi: Exactly. This is true. You mean the economic effect, right? Could they have gone worse?

Arvid Viaene: But like if we have the older politician with the younger politician and otherwise two similar provinces and the younger politician thinks I'm going to promote economic activity, but the result is that he didn't promote economic activity that much, but he now has worse air pollution.

Lorenzo Trimarchi: Exactly, indeed. That's what probably he found. Because I think of this patronage effect, they were still more likely to be promoted. So what we find that is interesting is that for mayors that eased deregulation, they were more likely to be promoted after the trade war, And this is quite a striking effect. Maybe easily. I didn't think about that systematically, but maybe it's linked with this pattern range effect that we found that is most concentrated by connected the mayors, our a result of regulation. So it seems that maybe, okay, you are in the network of the provincial leader. You follow the structure and then you get rewarded with the promotion, regardless of the efficiency of the measures taken in place.

Arvid Viaene: Which brings us to the point that sometimes, because I've been in environmental economics a lot, that sometimes when you need to make meet these air pollution standards, like PM 2.5, you install something. And then it drives up some costs. But uninstalling it is quite hard. So it's almost once you've installed it, it doesn't make sense to uninstall it as much, even though you've now lowered the pollution. And if you were to have the choice, you wouldn't do it again.

The U.S.-China Trade War of 2018

Arvid Viaene: Could you speak a little bit more about the trade war that happened? Because we've been talking a lot about the impact that China had, it happened in 2010. So could just maybe then provide some information to the background of what the trade war was about.

Lorenzo Trimarchi: Sure. The trade war, in 2000, we know that now we are living in a period of history in which we are all caring about the trade war because Donald Trump is also targeting European products and other products worldwide, and the European Union now struck a deal, and this was with the with the United States, this was involving environmental aspects as well.

The United Trade War, and especially the confrontation between US-China has deeper roots. So in 2016, Donald Trump won the election on a platform, fundamentally complaining about WTO and the World Trade Organization and the free trade policy of his predecessors before him. And I think at that time, I remember the environment. We were probably not taking these promises seriously that much, but actually we should have taken President Trump seriously. And in February 2018, Donald Trump launched a full trade war against China. This was unprecedented.

And it was unprecedented both for the scale, so fundamentally all manufacturing sectors to some extent were covered by the Trump tariff in 2018. And it was unprecedented for the tools Trump used. So Trump decided, I don't care about World Trade Organization rules. I think there is a national security emergency. We will adopt a new tariff. And this constitutes an interesting shock for us as a trade economist thinking about the environmental regulation in China.

Why? For several reasons. First, this was unexpected somehow in scale. Now we all know that this is real. We all know that this happened. But I remember very well the discussion in 2016, and I don't think many people were taking the threat of Trump seriously. Second I think what is a quite interesting for us is that there is a lot of heterogeneity in Chinese specialization industry specialization and this is what is giving us variation by the end of the day so fundamentally we use a bar what the economists call bartik research design so it is such design that takes a national level shock. These are the trump tariffs that affects equally all Chinese regions. But what it changed is the fact that the region regions are differently exposed to the tariff shock because they have a production specialization that differs from each other. So if I produce more relatively more steel and Trump puts a tariff that are higher on steel, now I will be more exposed than if I'm a prefecture that is producing more agricultural products that were not much covered by tariffs. So I'm less concerned about tariff this type of variation is what is really driving our identification strategy and that's what we exploited for analysis,

The size and impact of the 2016 U.S. Tariffs on the Chinese Economy

Arvid Viaene: I think it's a good point exactly that, 2016 was a different world. Maybe it wasn't just taken as seriously, whereas today it's much different. So what was the size of these tariffs?

Lorenzo Trimarchi: No thank you for the excellent question and indeed what probably most of people do not know because we think that now we are experiencing the most massive trade war, that also the first trade war was massive. And when you look at the period from July 2018 to September 2018, which is the month in which the Trump tariff reached their peak, we find that during the trade war, the U.S. imposed the tariff between 10 and 25 percent on around 200 billion worth of Chinese exports, And they affected almost 92% of Chinese exports in the industry. And to give you a sense of the size of the trade war, by September 2019 around 48% of Chinese exports were facing an increase in tariff, and these tariffs accounted for around 6% of Chinese GDP. So we are speaking about and massive shock to the Chinese economy.

Arvid Viaene: You said that the tariffs amounted to 6% of Chinese GDP.

Lorenzo Trimarchi: Yes.

Arvid Viaene: That's a crazy statistic. That puts it in perspective for sure.

Lorenzo Trimarchi: Yeah, no, this is big. This was big. We are talking about a lot of [impact]. The Trump tariff for China was a big shock. But I think because also because as economists we tend to study more the US economy that is a relatively closed economy. So do you have this bias. But trade is important for many countries. Goes

Arvid Viaene: I still remember at the University of Chicago when I was there and one of the professors , that's why we don't have very good trade, international trade economists in the US because and it doesn't matter to the US. Of course, it's not true, but he was, he was semi joking. But especially in the 70s and the 80s that most of these, the monetary policy would trade and interest rates. They're all international economists doing it..

Lorenzo Trimarchi: And it's one reason why in Belgium we care a lot about trade because Belgium is one of the most open economy in the world that they care a lot.

Arvid Viaene: So did this trade war end? Were those tariffs kept in place? Were they diminished at some point? How did the tariffs change over time?

Lorenzo Trimarchi: This is what people underestimate. Basically the trade war never ended. Somehow, I think they were partially removed by Joe Biden, if I recall correctly, in the aftermath of the Russian aggression to Ukraine during the inflationary spike. But in reality, this is a broader discussion about the trade war. But in reality, I don't know if I would conclude the confrontation between the U.S. And China is particularly driven by Donald Trump. I think what is different between the Republican and the Democrats is the trust towards multilateral organization, which is crucial also for our discussion on trade.

Retaliatory Tariffs from China to the US – hitting the Trump electorate

Arvid Viaene: I still want to pick out one thing of your paper, which is you've also studied the retaliatory tariffs from China to the US. But there you found no impact, I think, on these emissions. Could you speak to that?

Lorenzo Trimarchi: It's a good point. Fundamentally, these type of regressions are addressing, if you want, an omitted variable problem. There were also retaliatory tariff from China to the US. So maybe you can expect the reverse effect, because there China puts protection. This is a positive income shock. And then this will change regulation. And there we find no effect.

For me, it's unsurprising in the sense that if you think what the retaliatory tariffs were about, these were mainly soybeans and agricultural products. So this is, I think, the reason. So they were not really targeting polluted industry. While Trump was targeting steel, was targeting washing machines, solar panels produced. Those are energy-intensive industries. And under which the Chinese government might think rationally, okay, if I manipulate the environmental policy, I might change the path of growth for firms in these sectors.

Arvid Viaene: Yeah, that makes sense. I actually remember now because it was a big thing in America because the soybeans were, soybean farmers are a big lobby group.

Lorenzo Trimarchi: Yeah, of course. And there's beautiful paper in an economic journal by Timo Fetzer and Carlo Schwarz on the Economic Journal not showing on actually how the Chinese government were smart in targeting retaliatory products because they were targeting actually constituencies that massively voted for Trump. And usually, agricultural districts in the south of the United States are usually Republican areas. And not surprising, the Chinese were targeting these products.

Arvid Viaene: Yeah, I was in the US at the time and that definitely caught the attention for sure. I think the other thing why the size of the tariffs and the way you mentioned it is I think it helps me understand why there was an and such a re-

Lorenzo Trimarchi: Thank

Arvid Viaene: Why there was the effects that you saw in the paper. Because sometimes there are macroeconomic things that happen in productivity or growth slows down a bit or there's some, these things. But this is such a big shock that you would actually expect people to change. Because to some more minor macroeconomic shocks, you would not expect the Chinese politburo to redesign promotion criteria. Because it would just create a lot of uncertainty and people would be like , okay, what do I have to aim for now? But in response to a big shock that, you would, then it's more clear that there's some reallocation happening maybe among objectives.

Lorenzo Trimarchi: Of course, a maybe some experimentation. It didn't work for the economy, but they were trying several policy tools. We know that they were implementing massive subsidies. They were using monetary policy. So, I don't claim that environmental regulation was the only and, maybe not the main tool, in the end of the Chinese government to tackle this. We never pretended in our paper that it was. It was one of the tools and probably was not so effective, so that's what we learned in our paper

Arvid Viaene: Okay, well, that's actually a positive takeaway. I didn't quite get that yet this is a positive takeaway, that they weren't so effective in promoting [the economy through deregulation].

Lorenzo Trimarchi: It's something we should learn as a European as well. Now that we are under a trade war and we think about, there was there were discussion about the Competitive Compass in the European Parliament around one month ago in which President von der Leyen and the College of Commissioners decided to give less importance to environmental goals in their competitive compass, in their competitive goals.

Now I don't know, even in this setting, I don't know how much this will translate in concrete measures. Also because I didn't follow European legislation so strictly. But there is something to learn, right? If we stop caring about the environment, it's not that magically the economy will grow. Why? Because I think one of the strongest things we learn in international trade is that comparative advantage applies. So probably there are forced market forces that are so strong that the environmental regulation will not be able to change unless you do probably massive change in environmental regulation. And I don't deny this will have an effect, but you need a massive change in environmental regulation.

Arvid Viaene: That maybe brings me to another question. In the conclusion of your paper, you actually mentioned two potential takeaways. So you mentioned that your results cast doubt on using trade policies to address environmental problems such as the EU carbon border tax. And you also mentioned this Shapiro 2020 paper. Could you maybe speak to that, to what you meant with that comment?

Lorenzo Trimarchi: Yeah, sure. There are two points to be made. In Brussels, there is a lot of enthusiasm around the carbon border tax because it's a way to say, oh look, we have our current goal for our foreign policies, the access to the single market. So if foreign firms want to access to the single market, they should enforce the same level of environmental regulation as we do. Otherwise, they will pay a tariff. And I think our paper does not disqualify, does not invalidate this European policy approach, but just want to induce people to think more carefully about the spillover of increasing tariffs, because by the end, carbon tax is a tariff in developing countries or countries with weaker environmental institutions.

Because their reaction might be: if I need to pay a tariff anyhow, why not relax environmental regulation today to be able to enjoy growth, because anyhow the European will make me pay. So I think that we should more carefully think about the political economy in our partners when we set the trade policy, because what we learned in the Chinese case, that many developing countries at some point. If we see the Chinese case before the trade war, in the moment in which many developing countries will grow, we will put pressure for a green economy policy anyhow.

So I would be negative about trade as a way to promote growth and to promote better environmental standards. But I wouldn’t say either that this would be completely useless. I think as economists we should be always careful in drawing policy conclusion. But still I think our paper says it deserves double thinking on this issue.

Implicit subsidies to CO2 emissions due to Trade Tariffs

And then getting to the great contribution of Shapiro, which I think is a fantastic paper. I advise all graduate students to read the paper of Shapiro in QJE. Why I enjoyed the paper so much isbecause I think the author of this paper took a stylized fact we all know in international trade. Namely, that the input products enjoy a lower MFN tariffs compared to final goods. And then he took from the environmental economics literature the intuition that the input goods are also the more polluted goods. Then Shapiro in his paper makes the conclusion that we then are implicitly subsidising polluted products.

And this I found fantastic because those were two stylized facts that were there and this is how you are a great researcher because you had the two things known but then you put them together with great economics. And this is a fantastic paper, but I think it is the final part of his QJE-paper in the conclusion in his paper that he says: We should reform trade policy and we should increase tariffs on polluting products.

So if I understand this correctly, this is the proposal of Shapiro in QJE. And in this paper, in the conclusion, he himself says, there can be a political economy challenge that can be problematic. And I think our paper supports a bit this conclusion, and we believe, because, yes, it can be problematic if we start to go in world in which we increase tariffs.

Okay, yes, maybe the famous scale effect will be such that it maybe we'll produce less of these polluted products, but it's not straightforward, which will be the effect for regulators, and because there is still a demand for polluted products, and they might decide to act again on the cost function and to be competitive.

Arvid Viaene: Yeah. Awesome. Then maybe a final question is, has there been question that I haven't asked you? Is there something you want to talk about that I haven't asked you about that found important? Or is there something that?

Next Research Project

Lorenzo Trimarchi: I will do a small promotion for my next work in environmental economics. So this is, I think, a great idea to to conclude our interview. So I think this is a project I've always been interested in regarding political economy and the environment.

Because I think the biggest challenge for us, as I told you before, I think all politicians all over the world agree on the idea that a world that is cleaner is a better world. So I don't think any politician thinks it's good to pollute, it's good to live in in in a polluted world.

The point is the political economy. So is it, what are the incentives for politicians to enforce a environmental reform or greener policy. And now I'm happy to share that I'm working on an exciting new project with Alvaro Zuniga Cordero, who is a postdoc at the de Namur, and Juan Robalino from a University of Costa Rica, in which we ask a related question, but in this case for a democracy.

And what is the research question that we are trying to ask? Does climate change induce voters to vote more for green parties? And why we think it's relevant, because we believe there is a trade-off.

In a world in which climate change is active, we have more extreme weather events, and in this world, you might expect two things, we believe. One can be that when you meet a severe extreme weather event, I become more sensitive to climate issues, so I will vote more for green parties, or for parties that enforce green policies. On the other side, it may might an extreme weather event might be a negative economic shock for me, and as we observe in the recent populistic wave, you might be unhappy about the current parties that vote for populists, for parties that want to reverse climate policy.

We believe Costa Rica is an interesting setting for two reasons. One, Costa Rica is a country with enormous climate variability, and this will give us this type of geographical variation that we used in our China paper. And the other part of the Costa Rica project is that Álvaro Zúñiga Cordero, wo is my co-author in this project, collected a fantastic dataset in his JMP linking electoral data at a very granular level in Costa Rica, with employer-employee data. So I know in a constituency, the economic pattern, we know in a constituency, the economic story of a voter.

And somehow we can, at the macro level, see, first of all, how a climate shock affects voters, and second, test a potential mechanism. How the voters were affected by this climate shock. So I hope that we will get soon new results and we can speak together about these results in your podcast.

Arvid Viaene: I would be very excite, that sounds a really cool paper. And again, Costa Rica is a whole different setting with very finely tuned microdata it sounds. So I'm looking forward to that too already, Lorenzo. So thank you much for taking the time. I really, really appreciate. And thanks for coming on the podcast.

Lorenzo Trimarchi: Thank you, Arvid, and thank you for inviting me to this great initiative. We know need to know more about climate economics and what my colleagues around world are doing. So I hope you will continue to do this podcast. Thank you very much.

Arvid Viaene: Thank you.

Arvid Viaene: I decided to study economics when I was 18 because I believed economics has the tools to help improve our world. And one of the most exciting applications is the development of clean markets. Because these markets give citizens less polluted air while making sure firms stay as competitive as possible and thus keep providing jobs. Now, we know these markets have worked really well in the EU and U.S. But there have been questions of whether they work in emerging economies. But as we will discuss today, the answer is a resounding yes.

With my amazing guest Kaushik Deb, we will discuss the world’s first particulate pollution market, which was created in India in Surat. We will see that it created healthier air at lower abatement costs for firms. And, even better, that other cities and provinces in India are starting to adopt the power of clean air markets. As a warning, I get very enthousiastic during parts of this interview, but that is because I find these developments so inspiring, and I am sure my 18-year old self would agree with that. With that said, let’s dive in.

Kaushik Deb Depp is the executive director of EPIC India at the University of Chicago. He is an applied economist with more than 25 years of experience. He has advised governments and companies on energy policy, markets, and technology. And before EPIC, he led the India program at Columbia University’s Center on Global Energy Policy and held leadership roles at BP, IDFC, Terry, and the King Abdullah Petroleum Studies and Research Center. He holds a doctorate from ETH Zurich and a master’s in economics from the Delhi School of Economics. So, Koship, welcome to the podcast.

Kaushik Deb: Thank you so very much for having me. I really am looking forward to this conversation.

Arvid Viaene: Me too, because I’m very excited about today’s conversation because we are discussing what I think might be one of the most important and revolutionary developments in environmental economics recently. And that is the development of the clean air markets in India regarding air pollution—both what has happened in the past and what’s coming in the future.

I’m very excited to discuss that today. And to start off, I should mention for the listeners that I already did an episode with Dr. Krista Hasenkopf, where we discussed air pollution, but more from a global level. And we saw how air pollution is the number one global threat to human health. But air pollution in India can be especially bad.

So could you, to start off, talk about how severe air pollution is in India and what the impacts are on health?

Kaushik Deb: This is really kind of front and center in terms of what India as a country is dealing with in terms of its growth and development. India aspires to be a developed country in the next three decades. That involves a very significant increase in industrial activity.

But that increase in industrial activity also has consequent inputs on increasing fossil fuel consumption and energy consumption in general. How to kind of deal with that as well as environmental sustainability is really India’s central challenge today. According to the 2024 World Air Quality Report, 74 of the world’s 100 most polluted cities and towns are in India.

That’s— I mean, that’s a really sizable number.

Arvid Viaene: Yeah.

Kaushik Deb: And over 65% of them are located in the Indo-Gangetic Plain, which is this area of about 2,000 kilometers between Punjab and West Bengal in India. So it is a really, a really important piece— a geographical piece— to kind of deal with. And our work that Christa leads at the University of Chicago has kind of led to some very, very dramatic results. I mean, Krista did point out that air quality is the most important case— or the most important reason why mortality in our world is so high.

In India, on average, we are losing about three and a half years of our lives every year because of air quality. The city of Delhi where I work— this costs me nearly eight years of my life. Now, eight years of my life is a pretty chunky piece. You would agree, right?

Arvid Viaene: Eight years is a lot to lose, unfortunately. Yeah.

Kaushik Deb: And this is something that we kind of need to solve for urgently and immediately because our growth aspirations are also very urgent and immediate.

Arvid Viaene: So to tackle that, economists often prefer market-based approaches. Why do economists prefer those over, say, command-and-control regulations?

Kaushik Deb: Let’s take a step back, right? I mean, let’s not think about this just from an economist’s point of view, but let’s think of this as a societal problem.

Arvid Viaene: Yeah.

Kaushik Deb: Now, if there is a problem, what would ordinarily happen is that you would expect government or policymakers to kind of have to respond to that problem with anything that might be. Air quality is one. In this case, health might be another one. And the classic response to any of these issues, any of these problems, is: shut it down.

So if there is war in Ukraine, shut it down. If there are air-quality problems in Delhi, shut down the activity that’s causing air problems. But if you do think through that, what an economist terms— what that means is that the price of that particular activity or that particular pollutant or that particular externality is infinity.

And that’s not the case, right? We have, in some sense, an optimal level of economic activity that delivers an optimal level of prosperity and externality that we need to get to.

And that’s where the use of market-based instruments— pricing, markets, taxes— are relevant. Because as economists, what we are trying to do is make sure that the economic system runs in its most efficient and optimal fashion and is not a binary choice between on and off, activity happening or not happening.

We want an optimal level of economic activity that delivers the right amount of energy consumption and the right amount of pollution, delivering the right amount of economic services that we need.

Arvid Viaene: Exactly. I like that description a lot. And then maybe we could just jump into the air-pollution market. I think we can get to the story a little bit later, but I think just starting off with the results is very revealing.

So there was this air-pollution market— the market for particulate pollution— which was the first one worldwide, in Surat.

Kaushik Deb: Yes.

Arvid Viaene: Could you maybe talk about what the results were there?

Kaushik Deb: So this is a market for particulate matter that’s been running for the last five years. It was— over five years now. This was launched in 2019. And in 2019, this was launched as a randomized control trial.

The idea being that all economists of my type— they come from school knowing that economics solves all problems in life. And then when you kind of start to work with policymakers and the real world, you realize the real world—

So this is an exercise— this is an experiment that started 2019 in Surat, which is what you are talking about, where we set up this market and then carried out an evaluation of what this market would do through a randomized control trial. Economists of my type, we kind of come to the real world from school knowing that economics solves all the problems and then we realize that that’s not quite the case.

The real world is a very special case, and everything needs to be designed and delivered in a particular manner so that it can actually be implemented. That’s where this entire exercise came into being.

In Surat, a vast majority of the pollution problem comes from the textile industry that’s there. Surat is very well known for diamonds and jewelry and textiles. These are the two principal industries there. For the textile industry, we created a cap-and-trade scheme that was to be exercised over about 350-odd industrial units in that one town.

But knowing that this is a new solution and this is something that’s never been tried anywhere in the world— so the world’s first particulate-matter market, ladies and gentlemen, was launched and delivered in India and has been functioning for the last five years, as I said. To make sure that we were actually designing a solution that’s real and delivers answers and reduces pollution, we divided this industrial cluster into two groups.

So the control group stayed within the existing command-and-control regime, while the treatment group was put under a cap-and-trade scheme. And some of these results are so remarkable that you would kind of want me to— bring out the Quarterly Journal of Economics publication that Michael and his colleagues published earlier this year— you would kind of want me to re-verify all of those numbers.

The biggest result— I think the biggest result that the regulator was most interested in— is the level of compliance in the market. In the command-and-control group, the level of compliance was about 64%.

Which is really what the regulator wanted to solve for.Because in the market, the level of compliance was almost 100%. There was just one compliance period in which two industrial units did not meet their emission targets. And for the regulator, that kind of pretty much solves the entire problem, right? You are able to achieve 100% compliance to an environmental standard that you want to achieve.

What do the local people want? They want an improvement in air quality. And for every compliance period, the emission performance of the treatment group— the folks who were there in the market— their emissions were lower by about 20% to 30%.

So very significant and a chunky reduction in particulate-matter emissions that came from this particular experiment. Now, how do we bring industry on board?

You and I know this, right? Markets are an efficient tool. The whole point of efficiency is to reduce costs, to improve efficiency.

Arvid Viaene: Yeah.

Kaushik Deb: And the folks in the market were able to meet their targets at a cost which was almost 11% to 12% lower than the folks who were there in the command-and-control regime. So there is a very clear incentive for industry to be in the market, which kind of is also evidenced by the fact that once these results came out,

All of those folks who were not there in the market— who were in the command-and-control group— clamored to be included, to join the market.

And you would recall the Acid Rain Program from the U.S.

Arvid Viaene: Yes.

Kaushik Deb: I mean, that had a benefits-to-cost ratio of about 50-something to one.

Arvid Viaene: Okay.

Kaushik Deb: This city of 16 million— with this reduction in emissions, this improvement in compliance cost, this cost of whatever treatment plants, treatment systems that they needed to put in— this cost-benefit ratio is well over 200.

Arvid Viaene: Over 200, wow.

Kaushik Deb: So it’s— I mean, you can imagine the impact that this is having. And all of this took place without a single new dollar or rupee being spent by the Pollution Control Board. So no increase in regulatory capacity.

So what this experiment really kind of does prove is that, classically, we always think that market-based solutions are so complex, so complicated— how do regulatory environments with limited regulatory capacity deliver these really complicated solutions? What this market— what this experiment— proves is that these are the right tools to be used with limited regulatory capacity.

And these are the right tools that ensure that, with limited regulatory capacity, you can achieve the kind of emission performance that you want with lower costs. And lower costs, if you kind of think this through, are essentially an opportunity for industry to grow.

Arvid Viaene: There was so much in there. It’s like you say— there are six or seven questions I want to ask.

First of all, I think it’s like you say, the compliance went up to nearly 100% from, like, 64%, which is a really big success because that’s already— you know, there was no full compliance for a variety of reasons.

Then there was a lower cost to industry. Maybe my first question is, did the industry expect it would be lower cost, or did they have some premonition that some people could do it more efficiently? Or was there a lot of skepticism or hesitancy among companies? For example, in the EU ETS, companies always think it’s going to be this massive cost increase. Right? They’re worried about a massive cost increase in their competitiveness. So was there some sense that this would be the case?

Kaushik Deb: So to continue the story, we are now helping the state of Maharashtra, a bordering state in Gujarat, to set up a statewide SO₂ market.

So Surat was just the textile cluster; Maharashtra is going to cover the electricity, steel, cement, pet-chem, pharmaceutical, refining sectors. So— really much more diverse, and huge— I mean, really huge, huge industrial units.

Arvid Viaene: That is a big range.

Kaushik Deb: And as it happens, every time you take a new solution— a policy regulation— to any industrial group, there is an inherent resistance to saying that, hey, we’d like to try this out.

And for very obvious reasons, right? They think that this would lead to an increase in their costs of regulation. And who in their right mind, when you are a profit-maximizing private-sector business, would want to do that?

So what we did is we got the environmental-compliance folks in the company to start speaking to the finance folks in the company.

And the finance folks were the ones who realized that if we can improve our environmental performance to a point where we are much below the regulated standard, that gives me something that allows for a new revenue stream.

I can now monetize my improved environmental performance. So this is literally the textbook case of being able to monetize an externality. So it’s not an external cost anymore, or it’s not an external benefit anymore. It’s actually internalized in the profit-and-loss accounts of the company. And this conversation, once facilitated, became so central to having folks in industry come on board in the market. For example, there are industrial units who are using natural gas.

So now SO₂ emissions. Why would they join the market? Well, because they have no SO₂ emissions, and because they made the switch from coal to natural gas, they are now in a position to monetize the cost that they had to bear to make this switch. And this becomes a clear incentive for them to be part of the market. That’s one very big economic argument of how we brought industry on board.

But the second part is slightly more nuanced and something that you realize only when you’re seeing the market in operation and how environmental regulation is actually happening. There is a compliance standard— the concentration-based compliance standard— that’s there under the command-and-control regime.

If you do not meet that standard, you get a show-cause notice. And depending on your response to the show-cause notice, you are either told to shut down operations or do something to meet that standard.

If you do not meet that standard, effectively what will happen is that you would be told to shut down. And then you have to go through a variety of bureaucratic and regulatory processes to get back approvals to restart.

So, effectively, the cost is infinity. But in this case, we are creating a mechanism where you are able to meet that standard without having to be completely shut down.

Arvid Viaene: Yeah.

Kaushik Deb: So the folks in industry— the way they describe it is that in the previous command-and-control regime, my relationship as industry with the regulator, with the Pollution Control Board, was essentially adversarial.

Arvid Viaene: Yeah.

Kaushik Deb: But now the market has created an opportunity where we are together coming up with a cooperative solution which meets the regulator’s objectives as well as allows me to operate in an environmentally much more benign environment. So classically, we always think of markets as being competition and an adversarial outcome.

But now you have to start thinking of markets in this situation as something that is leading to a nice cooperative outcome that satisfies the objectives of all players— the regulator as well as industry.

And that, I think, is something that we don’t traditionally learn in Microeconomics 101.

Arvid Viaene: Yeah, it almost sounds like— the way you describe it— otherwise there’s this audit: “You were polluting too much.” Now you have to be worried. You’re already anxious. Do you have to shut down? There’s the whole bureaucratic process. Your company gets shut down.” Versus: there’s a market, and finance and environmental teams are talking to each other like, how can we make money off of this?

Like, “Oh, what can we do?” It just changes the dynamic of the discussion versus dread. People like to make money in companies, so it’s using that for coming up with better solutions.

Kaushik Deb: I mean, we are kind of creating a commodity, right? We have essentially commoditized this— the entire thing that economists love to do: that if only we had a carbon price, this entire thing would have been solved.

Well, we are creating a mechanism where you are finding a price for a pollutant.

Arvid Viaene: Exactly. And then— one thing we briefly… So one thing I think is also interesting to learn, which we briefly discussed before starting the recording, is how long it took the province of Gujarat to start this one, and then what the plans are going forward. Because being the first, there are naturally a lot of things that can go wrong or have to be taken care of. Could you speak about that?

Kaushik Deb: So Gujarat was an exercise that Michael Greenstone and his colleagues started way back in 2008–09. And if I add up every year that went into getting Gujarat up and running, I can easily think that this was an exercise that took about 10 to 15 years.

And this exercise took that long because this had never been done before, and every problem as it came up had to be solved. And this ranged from finding the right legal language for the regulation to identifying which emission-monitoring devices will meet these standards, their installation and calibration protocols, vendors who’d make this available, who would be the auditors for this, who would set up the trading platform, the data quality control and quality-assurance protocols— everything that came in there.

But having done all of that, we are hoping that the second market that we are going to set up now in the state of Maharashtra in India is something that we are able to do in a period of a year and a half or so.

We started this exercise last October. And my ambition is that we have this market up and running by the end of this year. In fact, what we are trying to do is, over the next few weeks, actually try and find ways of doing a soft launch of the market where we are able to set up the platform and have industries come and start mock trading, learning how the platform works, and everyone getting used to the fact that there is a new commodity in the market.

So from 15 years to 18 months is quite a steep improvement. And that’s the kind of learning curve that’s central to my ambition at EPIC. We talked about this briefly earlier. This is the kind of improvement in solar energy generation costs or wind energy generation costs that we’ve seen over the last 15 years.

Fifteen years back, solar used to cost a whole bunch of dollars per megawatt, and now it’s down to a few cents. That’s the learning curve that I’m attempting to replicate in the design and deployment of these markets. And over time, my ambition is that we have this as a plug-and-play solution available for jurisdictions around the world, where essentially it’s a matter of a few months instead of a few years in terms of designing and implementing a new market.

We are in the process of launching this as a formal initiative— a joint initiative of J-PAL and EPIC— during the New York Climate Week, and we’ve christened this as the Emissions Market Accelerator.

So fresh off the block, first one in the press that you get to share with this.

Arvid Viaene: Well, first of all, I would say this— this to me sounds amazing. Like, if you took my economist’s training — like, when I was young, this— you know, when you were in school, they’re like, “This is what economics can do if you do it right.” And you’ve brought it from 15 years to one and a half with the proven results, and you’re now doing it in other provinces.

Because I think the fact that there was this natural experiment that conclusively showed this can work and provide a lot of benefits for everybody. I got the sense reading about this— there’s this excitement to join or there’s this growing interest to join and apply these markets. I don’t know if that’s correct or not, or how would you see this development?

Kaushik Deb: So there’s— I mean, so this growth and this expansion that’s happening is both intensive and extensive. And let me draw that distinction. Once this experiment in Surat took off and delivered these results, now the default of the Gujarat Pollution Control Board for every pollution problem is markets.

So we are in the process of designing ETS schemes for— markets— industrial effluents for them for two central effluent treatment plants. So water pollution is being dealt with using these markets. They want to explore the use of markets for SO₂ as well. And we have a memorandum of understanding with them to think and start developing a carbon market for that state as well. So there is a lot of diffusion of the idea that markets can solve environmental problems across the board within that one state. But having seen that success, Maharashtra— the neighboring state— the SO₂ market that I talked about is well underway to use this as a tool and a solution to deal with their industrial-emissions problems as well.

We’ve just signed a memorandum of understanding with another neighboring state of Gujarat, Rajasthan, to set up an SO₂ market for them. This was signed at the last World Environment Day earlier this year.

And initial conversations with some other states in India are also happening. But if I were to put all of these three states together— if this was one big SO₂ trading program— this would be probably the world’s largest cap-and-trade scheme, much bigger than the EU ETS just in terms of population.

This would really be a hugely important and successful result. And seeing this now, there are conversations that we are having with numerous other countries and numerous other geographies and jurisdictions around the world on trying to use cap-and-trade schemes as solutions to deal with all sorts of environmental problems, including carbon markets.

There has been a trend recently— I would say a slightly aggressive trend— in the sense of a move away from climate regulation and climate management, especially using economic instruments.

But I think once some of these experiments and some of these markets become a lot more viable and grow, it will become a much more widespread tool. At this point, everyone in our community, in the environmental community, kind of thinks that cap-and-trade schemes are sophisticated and useful only in very developed jurisdictions like Europe and, in a pre-current-administration world, the U.S.,

Arvid Viaene: Yeah.

Kaushik Deb: But what we are doing is showing that this is a tool that’s much more widely applicable in the developing world.

Arvid Viaene: Exactly. Because when I read it, it seemed like there was a lot of— if we go back in time, like 10–15 years— a lot of maybe skepticism that this would work. So why do you think those skepticisms didn’t pan out? Or why did it work, in some sense? Why did it better than expected?

Kaushik Deb: So part of the reason is just ideology. I mean, this idea that markets are such a sophisticated policy tool that folks in the developing world aren’t smart enough to be able to use such a sophisticated tool.

And that was almost like a tautology. Markets didn’t work in the developing world because they hadn’t been tried. And once you did try and do that, this experiment showed that they work, and now it can be used and deployed a lot more extensively.

The second part of the story— and that I think is also very important to acknowledge— is that we’ve had significant changes and improvements in technology over the last 15 years.

Back in the day, the command-and-control regime essentially involved the inspector from the Pollution Control Board going to an industrial unit, climbing the pollution stack— the emission stack— taking a measurement in a thimble or some device, taking that little vial back to a lab, measuring what that vial delivers, and seeing whether that particular plant and that particular emission stack is meeting the standard or not.

When you have 340 or 350 industrial units in this one small geography, how many times in a year can you do that? And you get these results maybe once in a year, maybe twice in a year, maybe once in two years.

Even in the most sophisticated geographies and the most well-resourced countries— in Europe and the U.S.— there is a limit to how much capacity and how many people you can deploy to do this.

The cap-and-trade scheme that we’ve created and executed uses continuous emissions-monitoring devices that sit in these stacks and are network-linked to a central server that sits in the Pollution Control Board.

So the Pollution Control Board is able to get the emissions-performance data from each of these stacks on a 24/7 basis. We use a data protocol that allows us to take an average of 15 minutes and use that as a measure of whether they’re meeting the standard or not.

But this has been transformative. This is the reason why any Pollution Control Board, or any emissions regulator, any environmental regulator, would be interested in a scheme like this— because it gives them 100% visibility in terms of the emissions performance for their entire jurisdiction.

The second part of this is that in today’s day and age, having all of these networked to a central server that sits in the Pollution Control Board or the environmental regulator can now be very easily linked. And we can have these trading platforms developed pretty much in a matter of weeks, and we can have a trading scheme run seamlessly on a continuous basis. This day, during this day and age of big data, machine learning allows us to carry out a lot of this analysis on such a split-second basis that these markets are really, really much more efficient today than they would have been back in the day when trades in the stock market used to happen on paper.

Arvid Viaene: On a personal level, I admire Gujarat because I feel like they’ve been the main driver of this that has allowed this natural experiment to take place.

And then once other people see the success, then, you know, they get along. So are there some reasons you see— if I had an award, I would give it to Gujarat for the work they’ve done with the environmental— with the clean-air market. Is there something specific that triggered their openness or willingness to experiment with this natural market, or what led to collaboration?

Kaushik Deb: So a large part of that has to do with coincidence— the fact that there were existing relationships that Michael and his colleagues were able to leverage and use as the basis of starting this discussion in Gujarat.

I think there were conversations that were happening even then with a number of other states. And Gujarat’s first-mover advantage simply was that they were much more cognizant and wanted to get this pollution problem under control as soon as possible.

And when they heard that we could give them data on a 24/7 basis that they would own, that they would generate, and they would be able to use to whatever objective that they wanted to, they were, I think, the ones that first jumped on the bandwagon.

Having said that, I think this has now made such a compelling case that many other states and other jurisdictions outside of India are keen and very, very conscious of using a policy tool such as this, which is why all of these expansion conversations that we are having elsewhere in the country and the rest of the world.

But I think what’s very, very important— and that’s central to my mission at EPIC— is I don’t want this to be something that depends on individual relationships or ad-hoc conversations, or that someone reads about this in a newspaper or listens to your podcast and finds that this is a policy solution that they would want to explore and gets in touch and we try and see whether this works.

In a perfect world— an ideal solution— we would want this to be something that we are able to offer as a technical-assistance service to every jurisdiction in the world and then be able to carry out at least some assessment to see whether this is the kind of solution that works best for them, whether this is an appropriate solution for them, and be able to develop and design these markets so that they serve the best interests of those environmental regulators and those industrial units, without this necessarily being the current idiosyncratic process we have right now of doing this on a case-by-case basis.

Arvid Viaene: I think that’s a really great goal— exactly to have that offer ready, in the sense that people don’t necessarily need to listen to a podcast or news article, but it’s on everybody’s mind that this is naturally something you’d want to explore.

Kaushik Deb: And that’s— that’s the Emissions Market Accelerator that we will launch at New York Climate Week in September.

Arvid Viaene: I think I might just have to come to that just to see it at the next—

Kaushik Deb: I’d love to have you.

Arvid Viaene: This— I don’t know, this seems like the most exciting— anyway, you can see my passion for carbon markets. But I mean, I don’t have to tell you, probably. So—

Kaushik Deb: No, I mean, it’s completely infectious, and I know exactly why.

Arvid Viaene: It’s— the more— because I can even say, like, I did my PhD in economics. I’ve worked with Michael. And I read this article and I was amazed. Because it’s like you say, often you hear about markets— theoretically they minimize the cost. It’s also conceptual.

Because I think the other point is there hasn’t— like, the scale and the results are just so conclusive that you’re like, oh, this is what we kind of thought would happen even in a market like this, but showing it so— so nicely.

So I think we’ve covered a lot, so maybe two last questions. And you can choose how you want to order them. First, based on what you’ve seen or your experiences, what were the key factors in successfully— kind of— the cooperation between academic research or the economists at the university and the policymakers?

Because sometimes, like you say, there is a divide. Or sometimes you’ve got the consultancies who jump in, but this really seems like the collaboration between academics and the Pollution Board. So what do you see as the reasons that the academics were successfully supporting those developments?

Kaushik Deb: You see, because these are not traditional, classical academics sitting in ivory towers, in an ivy-lined New England school. These are academics who are embedded and delivering solutions with the regulators.

So my operating model is that we don’t write reports and papers. We do do that, but that’s not the only thing that we do. Our teams are embedded with the regulators— our teams are embedded with the environmental regulators, sit in their offices, design and implement these solutions in partnership with them, with their officers, with their inspectors— so that whatever is done is in complete reflection of what the environmental regulators need.

This is not a purely academic exercise, but a real-world exercise, and having our teams— our researchers— sit with the regulators is fairly central to delivering these solutions. And what that also does is gives me, as a researcher, the opportunity to learn from what the real world asks for and make course corrections and changes whenever I need to. So, for instance, a big reason for doing an SO₂ market instead of a PM market in Maharashtra is the fact that SO₂ travels. PM as a pollutant is heavier and sticks to a limited geographical area, but SO₂ can travel over very vast distances and is a precursor to PM.

So, in terms of impact, regulating SO₂ may perhaps have a much larger influence than just regulating PM. So these kinds of lessons, one has to make sure, are central in the design and redesign and the execution of the market.

The part that I think is also very, very important is that you have to make this entire process consultative and transparent. So you make sure that industrial partners, industry associations, the pollution regulators are all talking to each other and are not necessarily speaking at cross-purposes. So this conversation starts at the very outset with a stakeholder meeting, where everyone is introduced to this idea. And then, gradually, as the market design happens, you can— at each step— learn more about what each of these stakeholders need and are able to provide those answers to them.

So, for instance: How will the market work? What kind of a trading platform do I need to set up at my company’s portal? How will I be able to see whether all the industrial units are meeting their norms or not, as the environmental regulator? As a financial regulator, is there any kind of financial irregularity that’s happening? Is there anyone who’s holding these permits or not?

So all of these stakeholders have to be able to have full visibility and transparency in the way the market operates. And you have to do this at every step of the market design and execution.

Arvid Viaene: Got it. Okay, thanks for that. And maybe then, as a final question: Is there any topic you still would like to discuss that we haven’t touched? Or is there a question you wish I’d asked you— that’s still worthwhile mentioning?

Kaushik Deb: I think the most important part in terms of developing and executing something like this is that you walk into the room recognizing that you have to think this through and see whether this is an appropriate solution. So markets are an excellent solution for a certain type of emissions profile, for a certain type of industrial profile. Markets are not a solution for all sorts of environmental sustainability issues. So, for instance, in a congested urban area where a large part of the emissions are coming from the transportation sector, you don’t put in place a cap-and-trade scheme because monitoring and verification and monitoring compliance aren’t possible with the non-stationary pollutant sources.

Equally, if you have a very large industrial cluster, but that industrial cluster consists of very, very small manufacturing units, it’s hard to imagine that there will be enough emission-monitoring capacity that you can build to carry out a cap-and-trade scheme. But if you have a cap-and-trade scheme, it caters to emissions from industrial units which are stationary, where you can install these devices. So you have to answer all of these necessary conditions before you start designing the market.

The second part is also to think about the fact that we’ve come to a point— which we briefly talked about earlier as well— you come to a point where we recognize that all of these so-called sophisticated regulatory mechanisms that work in the developed world are now viable and available to the developing world based on a Global South experience that can now be replicated in other Global South geographies. It’s not something that necessarily requires a translation between the OECD and the non-OECD or the developed or the developing world and is based on experiences from limited regulatory capacity. And that, I think, is central to how we should think about markets going forward.

Arvid Viaene: And that’s also a very exciting way to conclude— exactly that they’re now available and hopefully implementable in three months going forward.

Kaushik Deb: Inshallah.

Arvid Viaene: So thank you very much for coming on. I really enjoyed this, and thanks for taking the time.

Kaushik Deb: Thank you. Thank you for having me. And this was a really nice and interesting conversation. I look forward to more of these.

Arvid Viaene: Thank you.

Hi and welcome back to the Climate Economics Podcast. I'm your host, Arvid Viaene. And in the previous episode we saw some essential climate calculations to calculate climate damages, and one of the key numbers for that calculation was the social cost of carbon, which captures how harmful climate change is. But we also saw that the social cost of carbon varied greatly between President Obama, president Trump and President Biden, going from $2 per ton of CO2 under President Trump to $190 per ton of CO2 under President Biden.

So today we are tackling the history of the social cost of carbon in the United States policy and why it has varied so much, and along the way we will tackling the history of the social cost of carbon in the United States policy and why it has varied so much, and along the way we will cover a lot of the things that go into it, as well as cover the work of Bill Nordhaus, an economist who got a Nobel Prize for his work on climate economics.

So let's start off with a refresher of what the social cost of carbon is. The social cost of carbon is the estimated economic harm from releasing one extra ton of CO2 into the atmosphere. In other words, what is the damage caused by one extra ton of CO2 to society, both today and in the future? But this is not just about climate models. It's about real-world impacts, such as lost agricultural yields due to droughts and heat waves, increased mortality from extreme heat, coastal damages, energy strain and so on. And here's also a key thing to know CO2 stays in the atmosphere for hundreds of years, so the damages unfold over decades, sometimes centuries. That means we need to think not just about today, but also about our children and grandchildren. So, with that said, let's go back in time.

Origins of the SCC in U.S. Policy

Let's start with the Reagan administration in 1981, when federal agencies have been required to assess costs and benefits of major regulations. But for a long time, climate damages were effectively valued at zero in these cost benefit analyses. That means that no cost to society was assumed from additional greenhouse gas emissions, and that can matter when you look at regulations regarding oil or renewable energy or anything else. But this changed after 2007 court ruling, where the Ninth Circuit Court of Appeals founded and I'm citing arbitrary and capricious end quote for regulators to assign a zero value to carbon emission reductions. Noting that quote unquote the value of carbon emission reductions is certainly not zero. So what to do then?

Well, the court's ruling encouraged the government to find a scientifically grounded dollar value for climate damages, and there had been early attempts under George W Bush administration, but there was no unified approach. Different agencies had different approaches and devised their own ad hoc carbon cost estimates, so that led to inconsistent numbers.

President Obama and the Interagency Working Group

But that changed when President Obama took office, because in 2009, the Obama administration decided to harmonize the process of setting the social cost of carbon, and this was done by creating an interagency working group on the social cost of carbon, for which the goal was to develop a single set of social cost estimates for use across the federal government, and the working group was explicitly designed to base that number on the best available science and economics.

So by early 2010, the working group, which included experts from the Environmental Protection Agency, the Department of Energy and other agencies, together in know Council of Economic Advisors and others. So it was a huge effort. So by early 2010, the working group released the first official social cost of carbon values, and the way they did it is they based it on three integrated assessment models that were developed in the academic literature at the time. The first was the dice model, the second was the page model, the second was the PAGE model and the third was the FUN model, and these were developed by economists William Nordhaus, chris Hope and Richard Tull respectively, and it's important to know that Bill Nordhaus got the Nobel Prize in economics for his work on the DICE model, because it integrated climate economics and macroeconomic models to allow for an estimation of the social cost of carbon. So this is some very seminal work that was then used during this process.

Integrated Assessment Models

So how do these integrated assessment models work? I think it's worth documenting the steps. First, the model needs to project future emissions, and you can do this using assumptions about population economic growth technology to estimate how CO2 emissions will evolve over time. Second, you need to model a climate response. So you need to translate CO2 emissions into changes in temperature, and this is a very science-based step, because then you need some models to convert CO2 emissions into increases in temperature.

The third step, then, is to estimate the economic damages from the increases in temperature, and this means that you need to assess how those increases in temperature impact various outcomes such as agricultural yields, health, flood damages and so on, and this usually happens through a damage function that links temperature changes to monetary damages.

And this is also one of the areas where there's been a lot of research since that time. I won't have the time today to go into it, but I might dedicate an episode to it in the future, because here there's been a lot of recent advances and what the impacts are in all these different areas. And a lot more microeconomic research has been happening in this area.

And then we have the fourth step, which means to discount future damages to the present value, and you can do that by converting future harm into today's dollars using a discount rate, and then, after you've done that, you can sum up all the damages to get to the total damage from one extra ton of CO2.

So the working group had three of these models and they ran each of them 10,000 times across various emission scenarios and assumptions, which then generated a whole distribution of these estimates. But the model's results were given equal weight in computing a central value and range, and for the year 2010, the central social cost of carbon was approximately $21 per ton of CO2. Now the working group also provided a low and a high bound, which was $5 and $35, respectively.

Now, over Obama's two terms, the working group did issue technical updates to the social cost of carbon, for example, the sixth and final update, which was in 2016,. The social cost of carbon for 2015 was about $36 per ton and the estimated value for 2020 was around $50 per ton. So it started at $21 per ton of CO2, but then, using several updates, for example, in the value function, in the end it became around $50 per ton.

President Trump’s approach: Higher discount rate and only U.S. damages

So now let's switch to President Trump's first administration. It became around $50 per ton. Upon taking office in 2017, he moved swiftly to dismantle or diminish the social cost of carbon's role in federal policy, and this was part of a broader rollback of climate initiatives. And in March 2017, for example, trump issued an executive order which disbanded the interagency working group and withdrew the official social cost of carbon guidance as not representative of government policy. Furthermore, the executive order directed agencies to revert to earlier guidance from 2003 for regulatory analyses involving greenhouse gases.

So what does that mean in practice? Well, in practice, agencies were no longer required, or even expected, to use the Obama-era global social cost of carbon values. Instead, they were instructed to focus on domestic impacts only and to apply higher discount rates. So that often meant 7% or 5% discount rate insensitivity, and the immediate effect was a drastic downscaling of the social cost of carbon values used for those federal analyses, and therefore the official position became that a ton of CO2 only would cause a few dollars of damage to the US economy, which is more than an order of magnitude smaller than the approximately $50 per ton of value used at the end of the Obama era.

Now, this huge drop was not because of any new signs showing climate change to be less costly, but purely a result of changing assumptions, because the Trump administration argued that prior social cost of carbon estimates were inflated and improperly included global benefits of carbon reduction that did not just focus on the American people. So by counting only domestic impacts, the Trump administration was able to ignore roughly 80 to 90% of the harm that a ton of CO2 would cause worldwide. So in essence, you could just ignore climate damages outside the US borders.

And second, by applying a high discount rate like 7%, you're able to very heavily devalue future damages to today's dollars, further shrinking the social cost of carbon by excluding global damages and using a 7% discount rate.

So the Trump administration obtained the social cost of carbon by excluding global damages and using a 7% discount rate, the Trump administration obtained social cost of carbon estimates that were near zero, on the order of $1 to $7 per ton of CO2. Now it is worth noting that the Trump administration's stance broke with the consensus of most economists and the international community, because, while many acknowledged uncertainties in the social cost of carbon, few support using a 7% discount rate for intergenerational environmental problems. For example, the Office of Management and Budget's own guidance recognizes that 7% is analogous to private sector returns and is generally too high for intergenerational public projects. Similarly, ignoring non-US damages was criticized because climate change anywhere can affect US interests through global supply chain, migration, geopolitical instability and so on, and because US climate action is generally predicated on the fact that if you help others, then the others will help you.

Nonetheless, the political motivation was clear. By lowering the social cost of carbon, the Trump administration aimed to remove the cost of carbon from regulatory decisions, making it easier to justify deregulatory actions that were a priority for the fossil fuel industry and then consistent with the administration's scepticism of climate regulations. Now, what about in court? Because these decisions were challenged in court, but legally the move generated debate but largely survived in the short term. There was not a specific court ruling invalidating the Trump social cost of carbon approach, though some Trump-era rules were later struck down on other grounds. But what is interesting is that many states and experts continued to use the more robust social cost of carbon estimates from the Obama administration even during this period. For instance, some US states, like New York, adopted the Obama-era social cost of carbon or even higher values in their own policy decisions, despite the federal pullback.

President Biden – from $51 to $190

So then let's switch to President Biden, who took office in 2021. And on his first day in office, which was January 20th, he issued an executive order re-establishing the interagency working group. And the working group was tasked with two immediate goals. First, to publish social cost values for CO2, methane and nitrous oxide in the short run, and these should reflect the Obama era approach. And then, second, it should undertake a thorough updated assessment to produce final new estimates by 2020. And his motive was clear he had a climate agenda, he rejoined the Paris Agreement, he regulated emissions and there was some need for credible estimates of climate benefits. So, within a month, the interagency working group released these interim social cost of carbon values, which essentially reinstated the Obama era central social cost of carbon, adjusted for inflation and for CO2, this came out to be about $51 per ton in 2020, using a 3% discount rate and again using global damages.

What about the update of the values that President Biden demanded? Well, in November 2023, the EPA the Environmental Protection Agency released a comprehensive report called the Report on the Social Cost of Greenhouse Gases Estimates, incorporating Recent Scientific Advances, and this is part of the regulatory impact analysis for a major EPA climate rule which targeted oil and gas methane emissions, and the report presented new social cost of carbon estimates using improved methodologies.

For example, one thing they did is they used a dynamic discount rate framework. So, rather than using a fixed discount rate, it applied a declining discounting approach over time, and so, as time goes on, you would use a lower and lower discount rates. It's a little bit technical, but it can have quite a bit of impact. The central case they used was actually around a 2% near-term discount rate, so Obama used a 3%, but then under Biden, it became a 2% discount rate.

So, as a result, damages went up, and then, for the modeling itself, they incorporated better damage functions. For instance, they explicitly modeled how climate change affects human mortality, which some of these previous models had handled in a very rough way and the results were striking. Had handled in a very rough way and the results were striking. Using a 2% discount rate, together with this declining over time, the social cost of carbon for emissions in 2020 was estimated at around $190 per ton. So this is roughly 3.7 times higher than the interim 51 value they had before. So one remark about that is the EPA's report noted that simply moving from a 3% to a 2% discount rate accounts for the majority of that increase in damages, reflecting how crucial discounting is, while updated mortality and other damage estimates also contributed. So we've covered the three precedents.

The Importance of the Discount Rate

I want to pause here and explain one key idea further, which is the discount rate. The discount rate reflects how much we value the future relative to the present. A high discount rate means future damages are worth a lot less today. A low discount rate means we value future harms almost as much as present ones. In essence, the discount rate is the inverse of the interest rate. The interest rate is if you invest money today, how much will it be in the future?

So, just to provide a framework, if I told you that climate change will cause a thousand dollars in damage in a hundred years. How much would that be worth to us today? Well, with a 3% discount rate, it's worth about $52. So, going from $1,000 to $52 today, with a 2% discount rate, it's worth about $138. And with a 1% discount rate it's worth over $370. But with a 7% discount rate, that $1,000 is only worth $1.2 today so much much lower. So you can see that the discount rate matters a lot.

So what are the arguments? Well, under the Trump administration it was argued let's use the 7% discount rate because that's an approximation of the rate of return in the capital markets. The 3% discount rate, which was mostly used under Obama, was used at the time and also proposed by the Nobel Prize winner, bill Nordhaus. The 2% discount rate was then later used under the Biden administration and there it was argued that this is the long-term risk-free interest rate, so that should be used. But I probably will do another episode just on this topic, because this is the topic that has been the most intensely debated in economics and policy. So I'll get back to this at some point in the future.

Wrap-up

So let's wrap up. Today we saw that the social cost of carbon is the price tag of one ton of emissions, but that it can vary greatly based on the discount rate used, the geographic scope and the damage assumptions. And then President Obama, trump and Biden use very different approaches, and so the estimate goes from $1 to $190 per ton. And the way then you would use the social cost of carbon matters, because it will really factor into cost-benefit analyses for policies, for investments and the way we value the future. So thanks for tuning in. I hope you enjoyed it. If you did, please leave a rating or share it with a friend. I much appreciate it and I hope to see you in a next episode. Bye.

Introduction

Hi, and welcome to another episode with me, your host, Arvid Viaene. And I’m really excited about today’s episode, Because today, I am doing my first solo episode and we are going to get to core of what climate economics is all about by talking about the harm of climate change.

Because climate change is happening. But we while we often hear general statements like, climate change will be extremely harmful, or, climate change is a major threat.

But to an economist, the question is, how much? How harmful is climate change? What are the damages expressed in monetary terms? Because as a society, we have limited resources. And the money we spend on fighting climate change, we cannot spend on other things like better healthcare or education. So there is a trade-off to be made.

So in this episode, I want to give you the tools to calculate the magnitude of climate damages yourself. And I am going to do that by giving you some emission numbers and some estimates of climate damages. And then in the next episode, I will explain more about what is behind those climate damage estimates and why certain estimates are more credible than others.

Essential climate Statistics

So let's start off with some essential climate statistics. First, do you have an idea of how many tons of CO₂ the average person emitted in 2023? Feel free to pause and make a guess. The answer is 4.7 tons of CO₂ per person. That’s our global average and our first key number. In addition, there were around 8 billion people in 2023. So if we multiply those two numbers, the 4.7 tons and 8 billion, we get about 38 billion tons of CO₂ emitted in one year. That is our second key number to know.

Now let's do the second part and move from quantities to damages. The key concept economists think about is the following: How much economic damage results from emitting one additional ton of CO₂ into the atmosphere? -- This is called the social cost of carbon — or SCC.

In other words: We emit one ton today, and that ton contributes to warming which creates damages from lost agricultural yields, increased mortality, lower labor productivity and so on. So economists estimate those future costs, discount them back to today, and sum them up. That would be the social cost of carbon. One number today that captures the damages to everyone on the planet for all upcoming years.

So to get a sense of the range of estimates, let's have a look at the United states. Because in the United States, governments are legally obliged to have some estimate of this social cost of carbon. Under Obama, the Social cost of carbon was estimated to be around $50 per ton. Now, you can probably guess which direction it went under the first Trump administration. That's right, the social cost of carbon estimate was decreased to around $2. Then Biden got elected, and an agency estimated the social cost of carbon at around $185 per ton. Under Trump 2, it’s currently been set to zero

So under Obama, it was $50, under Trump basically zero, and then under Biden it became $185. So these estimates vary substantially. And in the next episode, I will show you why these different governments obtained such different numbers and why some estimates are much more credible than others.

Meanwhile, let's also look at the European Union. There there is no explicit social cost of carbon. However, the European Union has an emission trading scheme. That means that companies have to buy permits to emit CO2. So the European Union essentially adds a carbon tax to pollution. And while I will discuss this Emission trading scheme in more details in the future, for now just know that the prices of those emission permits have ranged from €80 to €100 per ton of CO2 in recent years. And that number is in between the number of the Obama and Biden administration.

So the goal of this episode is to give you the tools to calculate climate damages. And now we have some statistics and a range of numbers, and that is enough to start calculating damages.

Back-of-the-Envelope Damage Calculations

So let’s run some numbers. Let’s say, for simplicity, that each ton of CO₂ causes a €100 in damage. (Euros)

And let's approximate the global average by 5 tons per person, that then gives us a total damage of 500 euros per person, per year.

Now, you can scale this up or down based on what you think is correct.

• If you think the estimate from climate change is lower, say €10/ton, then that’s €/50 per person

• If you think the estimate from climate change is higher, say €200/ton, then that’s €/1000 per person

Now, what about the the global level of damages? Well, we can do that too.

Multiplying our 38 billion tons of CO2 by a 100 euro gives €3.8 trillion per year in damages.

In addition, global gross domestic product, a measure of how much we produce, in 2023 was a 100 trillion.

So we’re talking about damages of roughly 3.8% of global GDP — all tied to climate impacts on current and future generations.

Now, again, this was an example of the calculation. You can then rescale the calculation based on your estimates of how harmful climate change is. For example,

• At €10/ton, the additional damage would be 380 billion euros, or 0.4% of global GDP

• At €200/ton, the additional damage would be 7.6 trillion euros, or 7.6% of GDP

So once you have the social cost of carbon and some emission statistics, it is straightforward to calculate climate damages.

Now, this damage estimate is not simply a matter of belief, but should ideally come from a rigorous evaluation of the damages. So make sure to catch the next episode where I tackle this. But the goal of this episode was to give you an initial feel for damages through ranges.

Additional Considerations

We now discussed the main calculation. However, I want to point out a few additional considerations. First, these damage estimates are averages. But climate change will hit some regions harder than others. If you want to learn more about that, I recommend my second episode with Harvard economist Ishan Nath where we discuss why the global south will be hit harder than the north.

Second, we have not taken into account the additional damages from air pollution arising from fossil fuel combustion. That was the topic of my interview with Dr. Christa Hasenkopf in episode 3.

Third, we have only talked about CO₂. There are also other greenhouse gases, like methane and nitrous oxide, which are much more powerful, gram for gram. But they do disappear faster from the atmosphere. Scientists have constructed a method to convert these other greenhouse gasses to CO2-equivalents. So if you do those calculations, Then the average CO2 per person would rise from 4.7 to 6.7 tons CO₂-equivalent per person. That’s about a 40% increase when we include those other greenhouse gases.

However, the calculations we did earlier are a bit trickier because these other gases are much more powerful in the short run, but also disappear faster. I might cover this in more detail in a later episode.

Regional Differences

A final point I want to discuss is regional differences. Because we only talked about global averages so far.

So let's start with the country that emitted the most in 2023, which is China. China emitted about 12 billion tons , or 32% of global emissions. But China also has 1.4 billion people, so that’s about 8.5 tons per person — nearly double the global average.

Then we have the United States. The U.S. emitted around 5 billion tons of CO2, or 13% of global emissions — less than China in total. But it has only 350 million people. So per person, emissions are around 14.3 tons — which is triple the global average, and 6 tons more than China

Now let's move on to India and Europe. India emits about 3 billion tons. The EU emits about 2.5 billion tons. But India has 1.4 billion people, and the EU only 450 million. So India’s per-person emissions are just 2.1 tons, which is less than half while the EU’s are around 5.6 tons.

And then we have Africa and South America which are quite similar in terms of emissions.

Africa emits 1.4 billion tons and has an average of 1 ton/CO2 per person. South America emits 1 billion tons of CO2 with an average of 2.6 tons per person.

Now let’s play with a thought experiment: If India’s per-person emissions rise from 2.1 tons to 8.5 tons, the level of China,, that would be an increase of 6.4 tons per person. Multiplying that by 1.4 billion people, and you get an increase of about 9 billion tons. That would make total global emissions go up from 38 to 47 billion ton, which is an increase of around 25% .

This calculation illustrates a significant challenge. As developing countries grow, their emissions are likely to rise because they want higher living standards like the rest of the world — even though historically, they’ve contributed far less to the problem. This tension is central to climate negotiations.

Cumulative Emissions

And let’s zoom out for a second. We’ve been talking about annual emissions. But what about the total amount of CO₂ we’ve emitted since the Industrial Revolution?

Take a guess. How many tons have we released into the atmosphere in total? [pause] Answer: About 1.8 trillion tons of CO₂ — or 225 tons per person, globally. That’s a massive number. And so we are adding 2% to that per year

Wrap-Up

Let’s stop here for today.

In this episode, we:

• Looked at how much we emit — 4.7 tons per person globally, and the massive differences between regions

• Introduced the social cost of carbon — and how uncertain, yet important, that number is

• Ran a simple damage estimate — with potential losses between 0.4% and 8% of global GDP

• And briefly touched on the importance of non-CO₂ greenhouse gases

In our next episode, we’ll go deeper into the economics behind the SCC — and why the different U.S. administration used such strongly different numbers.

Thanks so much for listening — and if you enjoyed this episode, consider leaving a rating or sharing it with someone who's curious about the intersection of climate and economics.

See you next time!