Michael Livermore 0:10
Welcome to the Free Range Podcast. I’m your host, Mike Livermore. This episode is sponsored by the Program on Law, Communities, and the Environment at the University of Virginia School of Law. With me today is Frances Moore, a Professor of Environmental Science and Policy at UC Davis. Her work focuses on climate economics. And she was the lead author of a recent paper in Nature that examined an important set of feedbacks between politics and the climate system. Hi, Fran, thanks for joining me today.
Frances Moore 0:37
Thanks so much for having me.
Michael Livermore 0:39
So let’s talk about this super interesting new paper that you published. Here’s a, here’s a great line from the beginning of it, I’ll just, I’ll just read it out. And the quote is, “climate policy and greenhouse gas emissions arise indigenously from the coupled interaction of the climate, social, political, and energy systems”. So there’s a lot of important stuff in there. Maybe you could help unpack it a little bit for our listeners?
Frances Moore 1:06
Yeah, I mean, there’s a lot of long words in there. But I think you have picked out like pretty much the key sentence kind of describing what’s new, in this paper and what what we’re trying to do, and the, you know, kind of recognizing that existing modeling, by and large, in the climate space kind of takes a missions as a given, right. So we’re either asking, you know, what will the climate system do given, you know, this emissions pathway or this other emissions pathway? Right, oh, wait, we’re taking these emissions. And we’re saying, you know, give me the like, lowest cost energy mix, that, you know, meet system, there’s some emissions constraint write that can get us to this, like a two degrees kind of consistent pathway. And what what both of those approaches do is they they kind of, they just say, like, Okay, well, this is emissions x, or its emissions y. And what we’re trying to do here is we’re actually trying to model the determinants of those emissions pathways. And so, you know, this is, you know, that it’s a key question and what climate change is going to look like over the 21st century of what happens to emissions. And right now, by and large, we kind of don’t put probability over those emissions, because mostly, we don’t incorporate them into our models. And so that’s what this paper is trying to do. So when it says endogenously, it means like, as part of our model, like we don’t impose emissions from outside of the model. Instead, what we do is we model the formation of policy and emissions, and that then links into the climate system, and then there are feedbacks into more policy and changes in emissions and so on as part of the model. And so that’s kind of what the key difference is, in this paper compared to kind of, like what most of the literature does.
Michael Livermore 2:57
Yeah, great. And so one thing that is, you know, I’ve always found interesting about the research in this area is there’s kind of a split between two broad ways of modeling, kind of the climate, economy energy systems. And there’s one that is very prevalent in, you know, like the IPCC process and amongst climate scientists, and that’s where kind of what you were saying is, let’s look at, you know, what happens to the, to the world on a particular emissions pathways. And, you know, there’s different kinds of scenarios. And that’s kind of about modeling how the climate system responds to, to what we’re doing in terms of emissions, or as you said, you know, like, what energy mix is consistent with different emissions pathways. And that’s kind of the the Intergovernmental Panel on Climate Change. The folks that put out the regular assessment reports, the big scientific process, and there’s a whole world of researchers and modelers who kind of feed their work into that. And then there’s another world, which is the which is the economist way of doing climate modeling. And that’s like your William Nordhaus who won a Nobel Prize in Economics a few years ago for his work, developing the first big economy climate model. And these are the models that feed into a different important policy process. Right. This is the social cost of carbon that’s developed by the US government that is used to price the value of emissions reductions, when the federal government and some states now use this number to when they’re evaluating policy using cost benefit analysis. So so how does the model that you’ve developed fit into these, you know, two broad categories of the kind of IPCC versus SCC approach to doing modeling of climate change?
Frances Moore 4:52
Yeah, that’s a great question. And so I’ve done work previously using that kind of the SCC type models. Like, you know, some of my work uses versions of dice and some of the other which is the Bill Nordhaus model and some other models that also do that. This is distinct, I think, from both of those approaches. It is similar to the kind of economists world in that, you know, in The Economist world, you have emissions and rise to some extent and dodge endlessly because policy entered into the model as a control variable. Right. So one of the one of the reasons economists design, you know, and use the models they do is because they asked this question about what does optimal climate policy look like. And using these models, where you’re looking both at the cost of emissions reduction and the benefits in terms of reduced climate change damages, you can have this objective function that then you, you know, you, you maximize that, that the welfare by controlling emissions at a certain rate over time, and that’s what that’s what dice does. We are distinct from that, in that we are not optimizing anything. So although kind of cost of mitigation, enter into the model, we’d have, we have no real, there’s no kind of centralized, you know, like social planner, the way there is in the data model, who kind of visit like omnipotent person who can just like, control the carbon price, every pick the global club and price every period, which we kind of know doesn’t exist. So what we’re trying to do is, our representation of how policy arises is a kind of more more grounded than that. And because of that, it’s like, certainly not non optimal. And so these carbon prices that come out of it are not necessarily optimal in any way. But that just kind of coming through what we think how we think the political process of work, basically.
Michael Livermore 6:57
Yeah, great. And I think that, you know, one way that I think of the work that you’ve, you’ve you’ve done here and published in the research mind is in some senses, as you said, it’s a third approach, or it’s at the intersection of these two different approaches. Because as you know, just to reiterate, the the Nordhaus and the economic kind of approach to doing this modeling is an optimization, modeling, right? What’s the ideal carbon price? kind of question is what they’re asking. And the IPCC world is doing a more predictive enterprise. What happens if we take this emissions pathway or that emissions pathway? And in some sense, it’s really interesting what you’ve accomplished here, which is to say, kind of a fully predictive model in the sense that what’s the most likely kind of suite of policies that we’ll see in light of what we know about how policy is made? Or at least how much of that we can capture in our models? And then how do those policies interact with admissions pathways? And then, and this is an important move in the paper, how do the emissions pathways then interact with the climate system to feed back into the political processes to generate different policies that then affect emissions and so on. And so it’s really a quite a quite a complete way of of making predictions about what our climate future looks like. It’s, it’s really fun and interesting in that way. So maybe, we could talk a little bit about that, that feedback effect that you now have been able to capture in your model where maybe just taking a step back feedbacks in the climate system we all know about this is where when you add carbon into the atmosphere, that could heat up, you know, that will heat up the planet, which then could do things like melt permafrost, which then releases methane, which heats up the planet. And, you know, that’s a positive feedback effect. But one of the feedbacks that you’re interested in is the feedback we’re effects in the climate system then introduce changes into the political system. So since what are some what are some of those feedbacks that you’re that you’re interested in?
Frances Moore 9:05
Yeah. So um just to respond to some of the things. You said that. So I think FeNi is comprehensive in its ambition. I would say that this model, the question of whether or not we are kind of, it’s also highly, highly stylized. And so I think that the covets, the ambition is to be comprehensive, you know, that, you know, there are pieces missing and that people approaching the problem from different areas of my kind of object to some of the simplifications we have to make, and there’s always kind of more we can do on that space. I think it’s also worth just spending a minute on why this is something we want to do. And this is not necessarily always obvious. And so I think for me, you know, this question of like, putting probabilities over different emission scenarios is really important if you approach the problem of an adaptation plan. No, right, and the fact that right now, we essentially don’t do that at all. And we say, you know, there’s no way we can tell someone about whether RCP 8.5, a very high emission scenario is less likely or more likely event, ICP 4.5 or ICP 2.6. Like, I think that’s just very impractical for people trying to plan for what climate change impacts are going to look like over the next 50 years. And I think we kind of want to do a better job of that. And if you do, then you have to start saying something about what emissions trajectories are more or less likely. And this is, there are other ways of doing it. But this is kind of one way of doing it. But then you have to get your question. So what we’re trying to do here, the reason we have a lot of feedback processes is to kind of respect the fact that there is a lot of potential non nonlinearities in the system, and that we can represent them in terms of the these feedback processes that lead to when you coupled together a lot of different feedback, you can get quite complex kind of emergent dynamics out of a model. And so we really paid attention to evidence for these different types of feedbacks when we were looking into the relevant literature’s and we tried to capture kind of as many as we possibly could, in designing the model, so that, although it’s highly abstract and stylized, it hopefully represents a lot of some of these key processes that are going to kind of affect the dynamics of these trajectories over time. And so some of the examples, you talked, you mentioned, the feedback from the climate system, kind of back into the social system. And so this is a overarching feedback that goes across the whole model, and we call it that cognition feedback. And so this is the idea that, well, you know, maybe people perceive climate change. And you know, that perception of climate change maybe leads them, you know, and this is something we vary in the model. But maybe that perception of climate change leads them to kind of either support climate policy or undertake kind of pro climate like individual behaviors. And so that’s one of the big feedbacks that we allow for, and then we allow for various types of like imperfect cognition, as supported by the like, that that piece of the psychology literature, there are other important feedback some of your listeners may be familiar with, like in the, in the energy system, for example, the feedbacks associated with cost declines over time. So kind of new energy technology, they’re often very expensive. But then if you kind of deploy more of them, the costs come down, which means you deploy more of them, which means costs come down. And this is reinforcing feedback. That’s quite well documented in the kind of energy systems literature. And so like, that’s one of the feedbacks we have dead about, I think altogether, about seven or eight of these different types of feedbacks.
Michael Livermore 12:48
Yeah, there’s, no, there’s a lot of interesting stuff there. And maybe at some point, if we have time, we can get back to I think there’s a kind of a fun and interesting philosophical question, actually, at the heart of your approach about kind of, you know, modeling human behavior in this in this causal way and making predictions that is pretty interesting, actually, deep kind of philosophical differences between the Nordhaus the IPCC and your approach, but but just maybe to stay with the in the weeds of the model for a second before we zoom way out? So yeah, so I took a look at me, just the different feedback processes that struck me in the in the paper, we’re, you know, this notion of social conformity, right, the idea that if a bunch of people get together and, you know, start really caring about climate change, and showing that, that there’s a norm that develops around addressing climate change that that could have potential tipping point effects. In you know, we have experience with that maybe with smoking where a norm develops around, say, smoking indoors, and then you know, there’s kind of a tipping point where it used to be if you were didn’t let people smoke in your apartment, you were kind of a big jerk. And now, it’s pretty strange if someone lights up in your house, without asking. You noted that climate change perception, right, is that as we start to see climate change happening in our environment, then you know, that might lead people to care more about climate change, recognize it. political interest is another one that you noted. The one that as a law professor, I I struck me interesting as the expressive force of law feedback. We don’t normally see that in scientific papers. So maybe that’s something we can talk about a little bit. And then another important one is the temperature emissions feedback where if, if you have temperature change, that then leads to a reduction in economic growth that’s then going to affect emission. So all of these are really interesting on their own and, and could be and we could spend a lot of time talking about them. Maybe we could talk a little bit about them. I’m just thinking, well, actually, what why don’t you tell me what what’s your favorite feedback?
Frances Moore 15:06
Given given, I’m talking to a law professor here would be really interesting to talk about this expressive force of law piece of it, I think, you know, because that is, that’s an example where something was some of the challenges we had was reading some of the literature and the literature with some and the psychology literature, to some extent, and politically, is really importantly, the political science literature, where you have documented feedback that are clearly important to the system. But they’re very qualitative, they tend to be very qualitative district description. And so and what we have to do on this model is I mean, it’s a computational model. So you have to kind of take that, and you have to try and like turn it into into functions and numbers in some way that you can like, plug that idea in to your modeling of the system. And certainly that expressive force of law was really kind of interesting when I when I kind of learned about this idea. And it was clearly an important potential feedback, right? If you have signalling power from changes in the law that feeds back to public opinion in this reinforcing feedback loop, then that’s going to quite be quite important in changing the dynamics, potentially changing the dynamics of the system. And so we wanted to incorporate that in a way that, you know, drawing on this literature for support, but again, very qualitative literature, mostly with some case studies, maybe. But we kind of, you know, we wanted to be comprehensive in terms of the potential pathways that we were including there.
Michael Livermore 16:36
Yeah, no, I think it’s great. I mean, I’ll kind of offer two somewhat contradictory takes on that. So one is, I think it’s great. I mean, and it is, you’re right, that it’s a very interesting potential feedback could be important. There are lots of my colleagues in the legal academy who are interested in the idea of this expressive force of law, or sometimes, kind of think of it as like, using law as a mechanism to achieve kind of cultural change. You know, rather than just changing, you know, incentives or something like that. So, you know, my own personal take on this is that I’m I’m a bit of a bit of a skeptic, there’s kind of two different takes on expressive, you know, the kind of expression in law. So one is just more kind of moral, that that it’s really, irrespective of how the law affects people’s attitudes, or beliefs or preferences, you know, that the law should respect equality or something like that, like, embody respect for gender equality, or racial equality or something like that. That would be one that’s more of a kind of a moral view. And then the alternative would be like the social scientific, or the behavioral view would be, you know, when you have an judicial opinion, like Brown versus the Board, or Obergefell, which was the gay marriage opinion, then, you know, that that affects how people view things like racial equality, or, you know, marriage equality or whatever. I think there’s just a big open question on how much that works. How much that’s that’s real. You know, that, as you might imagine, it’s completely endogenous, right. So like, there’s other social forces that are acting on the court, and they’re acting on politics and are acting on culture that, you know, those social dynamics could be leading to broader social change and leading to the judicial opinions. Right. And it’s super hard to dissent. I mean, basically, super hard slash impossible to disentangle those, you know, you’d have to imagine the experiment. Right? You know, you’d have to somehow, you know, have some kind of exogenous shock, that led to these kinds of legal changes, and then you try to have to trace, you know, imagine, you know, again, it’s like, it’s just a theoretical kind of study that you would do. So, yeah, so I think that there are just different views about that. I’m probably more on the, on the skeptical side, on the on the behavioral side, I think on the moral side, that’s a different question. But on the on the behavioral side, I’m somewhat more skeptical. It’s possible, it’s just very hard to know. That’s the kind of thing it’s you almost, there’s almost no way to empirically know anything. So it’s kind of based on people’s views, or you can do things like you can run experiments, or survey surveys, I’ve seen some of this where you kind of inform someone of a hypothetical or use prime someone, letting them know that there’s this judicial opinion that says this, and then you do like an A B testing kind of thing where you expose some people to the judicial opinion and not others. And you see how that you see if that’s has any effect on their views? I think the out of that literature again, it’s a bit of a mixed mixed story. I’ve actually seen some work that shows There are reverse effects. Right? Like, you know, for example, like an interesting one would be I don’t actually know if this has been studied specifically, but you could do this would be, you know, is waterboarding torture would be a question and you could say, expose people to a hypothetical judicial opinion that says that it’s yes, and see what the effects are. But again, I just, you know, I think the I think out of literature, what you get is, is very, very mixed, and again, sometimes even even inverted. So like Roe v. Wade, for examples,
Frances Moore 20:32
I was just gonna say Roe v. Wade, I think it’s a classic example of like, the feedback operating in the opposite direction, right? Attention, right? Yeah,
Michael Livermore 20:40
exactly. Where it was actually pretty uncontroversial the decision at the time, and then it just kind of became more and more and more controversial that more and more and more, but it? Well, it did, and then stabilized into kind of the current level. So yeah, but I do think it’s the kind of thing that’s it’s, and this actually is very interesting, this gets us into models in general, and how to read the results of a model, like the one that you have, is, it’s a very useful thing to have in there, because it’s a possible pathway. And if someone believes that they express the force of law is a real and important phenomenon, which they totally can, based on current evidence, it’s just, uh, you know, it’s just what’s your model of human behavior and how it interacts with legal institutions, then, you know, they can look, you know, in theory, you can imagine, you know, you can kind of press that dial or not press that dial, right? Do you think it’s important? Do you not think it’s important or look at the model runs where, you know, where expressive force of law is a major factor, you’ve turned the dial up or look at the model runs where that’s low on the, you know, where you’ve turned the dial down? And then, you know, that can tell you something about, you know, if it’s a real thing, how important it is. Right. And so I think that even irrespective of the kind of current state of affairs in terms of the empirics, there’s, there’s value in modeling something like that.
Frances Moore 21:58
Yeah, I think that’s definitely, you know, the approach, we took it that, you know, we allow for the feedback, and then, you know, it could have a value of zero, and it does in some runs. And then, you know, just the fact that it’s a feedback process, which is what we, you know, that by itself creates these empirical challenges that you were talking about, where everything’s connected to everything else, right? So if you’re looking at the real world, like, how do you say, what’s the causal effect of the feedback versus not? Well, it’s really hard, right? Because, you know, the, the original policy itself, like a rise of endogenous we like from the society that producing that policy, right, but then it feeds back, potentially feeds back in some way on that society. And so, you know, this this modeling approach allow for a lot of like, hypotheses around what, like human behavior and cognition and social interactions, and how they aggregate up to produce policy allows for you to put in a lot of different models of how that works. And to kind of like, look at how that affects the system affects emissions. And I think we don’t necessarily take strong positions, either way on like, exactly what the magnitude of some of these feedbacks are, we have, you know, but what we’re trying to do is to the best, we can kind of integrate across the evidence allowing for a lot of these interacting dynamics, and say something, hopefully comprehensive about what the emissions pathways look, and what factors are important in driving those emissions? You know, so if you look at this parameter, say, the feedback, for example, and you decide, oh, you know, what, like, it turns out, it doesn’t seem that important. After all, well, maybe we don’t need to spend a lot more of like, empirical evidence, you know, EFA, if we, you know, just for if we’re only interested in climate change, which obviously, we know, is interesting for other reasons, but we might focus our efforts on kind of other other premises that drop out. And it’s been really important in differentiating these pathways.
Michael Livermore 23:51
Right, right. Yeah. And that’s how, you know, super, super useful. And, and, and kind of the purpose of modeling exercises like this, one of the actually one of the outputs, or conclusions, or at least tentative conclusions that you guys come to, I think that’s pretty interesting, kind of had to do with the effect of individual behavior. I don’t think this is maybe all that surprising for at least some folks who follow this conversation closely. But it looks as though you know, basically, individual behavior can matter. But only kind of when it leads to broad preference cascades of some kind, right like that, where my behavior then affects someone else’s behavior that then affects someone else’s behavior. And then we reach a tipping point, norms change, and that leads into, you know, feeds into the political system and everything else. So it’s by myself, I’m not going to be able to accomplish much and so the real question is, kind of how much does our individual behavior or the behavior of individuals who are concerned about climate change actually affect the behavior of other people? So was that a fair or conclusion to come with come up with? And I’m just curious about that. Yeah,
Frances Moore 25:03
that that that question about individual behavior, I think that was part of, you know, we have a quite rich like representation of like individual behavior change in the model. And partly that reflects, you know, where some of the effort has been, I think, on the scientific side around like, modeling kind of individual effects, kind of individual decisions do kind of pro Environmental behavior. There’s a lot of work on there, that we try and kind of incorporate in. But, you know, there’s this tension, I think, and you saw, so these debates are playing out, I think, in some of the popular kind of articles and things about, you know, the focus on individual behavior change versus on some kind of collective action. And what we do here is we try, and we, I think we were able a little bit to kind of resolve some of the arguments at those debates at a higher level in the sense that we, we find, and this is not surprising, right? Like, you know, just individual behavior change, like, by itself, it’s like, you know, that cannot solve climate change, right, because most of how we produce emissions is collective, and it’s a collective decision. And so, you know, people making making changes, like, are only able to do so much to actual emissions. But because we have a lot of these reinforcing feedbacks in the model that are all coupled together, it is possible to put the model into certain states, where the propensity of individuals that support collective climate policy to kind of make costly changes in their own behavior, have a feedback, to their neighbors, to their social network, that persuades other people of that same opinion that we should do something at the collective level to address climate change, that had an effect on the political system. And because of this all live like coupled, connected, reinforcing feedback that can create those kind of cascade of action, that can lead to a kind of a tipping point. And I think, like focusing on that piece of it, that that what you’re doing there is like a social signal, not it’s not necessarily the emissions reductions themselves, you know, but it’s that social signal of, you know, I am under about your values, right? And it’s kind of thing like, I am undertaking this action, that’s costly to me, because I care about climate change for the following reasons, right. And I think other people should, too. And that effects that can potentially kind of leverage those individual actions into kind of much more large scale changes. And so we kind of show that like, the model has this have the potential in it? Once we parameterize, the model to like, look something like more, you know, what we think might be a more realistic set of parameters, it turns out that those states of the model where individual action is like, really key and tipping the whole system into this, like sustainable state of actually quite. It’s not so common. So it turns out, like when we actually like to do our real model runs about what we think how we think things might evolve, it’s not so important, but I think, you know, some of that debate comes from people’s intuitions about that social signaling value. And that, you know, it is real, and it can drop out of the model in certain states.
Michael Livermore 28:18
Yeah, yeah, no, it’s super, super interesting. And I think, just to kind of get into, you know, some of the some of the other results, or insights that we might get out of the model. Well, maybe maybe there’s a kind of a top line thing, and then we can get into the details. So one top line thing that I took his again, I’m gonna kind of read a sentence, and then we can unpack it a little bit. Because something like this, there it goes exactly like this is the quote, are parameterised model implies a high likelihood of accelerating emissions reductions over the 21st century, moving the world decisively away from a no policy business’s usual baseline, which I believe is economists speak for, you know, this, there’s hope. And so maybe you could just say a little bit about that finding, and then how you kind of come to it. And then and then I think we can move into some some more details about the relationship of these different outputs and scenarios. And so,
Frances Moore 29:15
yeah, so so, you know, you’re right, that that is, you know, really one of the headline conclusions of, you know, our whole exercise here and that. So, the, the, how we get to that point is we start with a model that has a lot of potential dynamics in it, you know, that can give rise to a lot, you know, a lot of potential behavior. And then we, we do some exercises to try and constrain some of the parameter sets, and that the two main things one is that we, we use kind of evidence on the current distribution of opinions on climate policy. And so that comes from some pew surveys from mostly from kind of us OECD kind of set to come trees. And that’s a kind of key starting place for our model. And then we also do some exercises where we we kind of run the model in kind of, you know, historic mode. So looking at kind of the last decade, and we probabilistically constrained some of the parameters based on how the output from the model matches what actually happened. And so that helps us rein in to some extent, the parameters. And in particular, we’re able to do that, in parts of the like the system representing the political component, very importantly, in front of the system representing the energy system. And other other parts of the model, like less well constrained, but we take this probabilistically, and then we run the model, like 100,000 times sampling over these uncertain kind of parameter spaces. And then we take, we look at what the trajectories of emissions look like under those 100,000 runs. And that’s, and we find that in a large fraction of them, we see this kind of accelerating climate policy and dropping emissions. So that in our kind of central case, what we call the modal pathway, you get to global net zero emissions, world zero emission, you don’t have negative emissions by about 2080 to 2090. And so that is not a kind of quite a two degree consistent pathway, but it’s also not far off from it. And so that would get you to something kind of close to above, you know, about 2.3 degrees by 2100.
Michael Livermore 31:40
As in a point that you make in papers, this is like roughly consistent with, actually the policy commitments that are kind of on the books that we get out of the Paris accord and pledges that that have been have arisen out of that. And then obviously, you know, there’s been some talk of maybe adding later out into the century, or at some point when we develop the technology, some kind of negative emissions to keep us below two degrees. So that’s pretty interesting, because you didn’t plug in those policies, they actually came out if your model.
Frances Moore 32:10
Yeah, that was it was very exciting when we discovered that, because it is quite surprising, right? That, you know, we don’t, there’s nothing about these policy commitments in our model, our economic policy is just arriving as an output from the model. And yet, our modal pathway looks very much like what the what the 2030 2050 kind of emissions commitments looked like. And actually, there was a just a paper, another paper in Nature last week, showing that the long term net zero commitments that countries have made are largely consistent with a two degree pathway. And so that’s what we’re kind of able, we seem to be able to capture at least some of those dynamics, you know, whether or not countries are actually going to meet that, those those long term commitments? Like, you know, we can’t say but you know, our model suggests that they might not be far off from it.
Michael Livermore 33:13
Yeah, ya know, that that is, you know, that is, that is good news for that, and certainly good news for a model, when you can kind of put in, you know, the inputs on one side, and then you get outputs that actually match something that looks like the real world, which is pretty, I could imagine, was pretty exciting. Kind of on the other side, the you know, there’s always there’s always some bad news, whenever you do climate modeling, right, there was, you know, there were some model runs where you had higher temperature change, popping out, you know, something closer to, you know, three to four degrees. And, and it’s interesting to think, consider the model features that were associated with, you know, kind of more or less temperature change. And so I’ll just read off some of these that struck me. So in the in the kind of bad world. What leads to the bad world, or in some sense, is things like, Well, what you write here is high network comm awfully. So what that means is that people are essentially separated into polarized camps. And so the people who like care about climate change and do take efforts to address climate change, that that message doesn’t spread very effectively through social networks, because because the social networks are essentially fractured, and amongst people who think like, high social norm effects that people are strongly affected by the people who they’re around, but they’re around people who they tend to agree with political systems that have a bias towards the status quo. A couple others that I think is quite interesting, also is high we write high bias to simulate assimilation. So what this means is that people and there’s some evidence that this is the case, when there are severe I read that weather events or other things like that. People view those things through a partisan lens. So people who believe in climate change or in the US are Democrats, they’ll say, oh, there’s wildfires. That’s because of climate change. Other people who aren’t big fans of the idea of climate change or consider themselves Republicans might look at the same thing and say, No, that’s because we haven’t like managed our force properly. And then the shifting baselines issue, right, which is, that’s kind of our frog in water. Example, right? Where, if we’re just comparing temperature to the last, you know, five to 10 years, it doesn’t really look like it’s changed all that much, right. Whereas if you look over longer time horizons, than it does look like it’s changed quite a bit. And the reality is that humans tend to update their views pretty rapidly, they tend to adapt, which generally is actually probably a good thing about us. But it makes it very difficult for people to see long term trends. So maybe we could just talk about some of those, those those factors and how they relate to the, to the model to then generate these outcomes of more pessimistic climate scenarios.
Frances Moore 36:09
Yeah, so So kind of broadly speaking, you know, what our model is doing is, you know, it’s taking in evidence, which is coming from the Pew opinion surveys, that there is fairly already across the OECD kind of fairly widespread support in general for climate policies, and that, and that’s kind of a starting point. And so then you have to kind of in order to get into these, like bad states of the world, you have to kind of explain that there needs to be reasons why that doesn’t translate into kind of climate policy. And broadly speaking, broadly. So there’s several reasons why that’s the case. So one reason is that the deep kind of social set of reasons, which is you have a fractured social system, where, you know, it’s that, you know, we’re just going to this, this distribution of opinion, it’s just going to kind of stick in place, and you’re not going to get this like what the model would otherwise want to deal with this kind of broad, like transmission of support for climate policy, have it spread through the population, there are another set of reasons to do with responsiveness as a political system. And so there’s different if you know, if you have broad support for climate policy, but you have a fairly unresponsive political system where that just doesn’t matter in terms of like, collective action. That’s another reason why you could, you know, end up in a world with not not very ambitious climate policy. And then there’s another set of reasons to do with the feedback of cognition, right? So even if you’re not persuaded by people in your social network, right, so the pathway in the model where you could just directly observe climate change, right? And so if you and it turns out, if, if you allow that to happen, with no, no kind of limitations on people’s cognition, then basically everyone supports climate policy, like right away, because the evidence the evidence of climate change? Well, not, you know, certainly going forward is like, very, very high. But we know, we think that that probably quite a lot of limits to how people are able to perceive climate change, given their observations of weather. And that includes things like shifting baselines, which I’ve done some work on, before, using using Twitter data where we suggested that people, you know, adjust their sense of normal on about a five year basis, and like, the signal of climate change is not very high on that, on that timeframe. And then you couple that with this, this bias assimilation effect, too. And you can get a situation where people, you know, people are not able to distinguish the climate change signals at all, given given their observations. And then there’s one final reason for why you might end up in the the worst day for the world. And that’s to do with the energy system. And if you end up in a world where you just get really unlucky in terms of the evolution of energy technologies, and they just don’t keep evolving the way they have and like you, they they’ve stay really expensive. And so even though maybe your climate policy is quite ambitious, it’s just you’re just not doing much in the energy system. That’s another reason you can get these, you know, sit drawers on this, the higher end of warming. And so we’re kind of can distinguish those pathways to some extent, by looking at, you know, the combination of model parameters that produces different different combinations of climate policy and emissions of the 21st century. Yeah,
Michael Livermore 39:34
you know, you know, for what it’s worth, I’m probably more optimistic about the technological side and the social side. I think we have reason to be in a sense, right? If we, if we just look at the last couple of decades and technologies come along quite quite nicely. Our politics have not nearly as nicely so I’m curious about some other what What’d you think of some other potential feedback effects and then curious also, if you just if you were the future kind of work on this, on this model, and this approach is going to take you. So some of the, the feedbacks that I’ve written a little about a little bit about in this area are the ways that the, the climate system, or changes in the climate system could kind of do harm to our ability to carry out political change. So I think, you know, one of the things that’s interesting about the model that you guys have is, it’s pretty optimistic in the sense that, as the climate starts to get, you know, as climate damages become apparent, that, generally speaking, through mechanisms that you guys identify, leads people to care more about climate change, which is pretty sensible thing, right, is that people see that something bad happening in the world, they care more about it. The concern that, that I’ve raised with it with a co author, Peter Howard, is, you know, this idea that, in order to address climate change, you need to have a fairly high degree of cooperation in society. Because, again, no individual actor, including any individual country can really substantially change the emit global emissions pathway. And so there’s huge free rider problems, and those aren’t going anywhere, there’s always going to be free rider problems. And so some form of cooperation is necessary. And the concern is that climate damages, undermine the conditions that are necessary for that kind of cooperation. You know, by just putting pressure on societies, like massive mass emigration, economic costs, social dislocation, you know, all the harms that are associated with climate change, those just decrease the capacity of the state to do, you know, big projects and decrease the ability for international for international cooperation or the functioning of international institutions. I’m curious whether you guys contemplated that kind of downer of a feedback and or if it sounds kind of roughly plausible, or something that could be potentially incorporated into the model.
Frances Moore 42:17
Yeah, it’s definitely something I was thinking about. I think we, I definitely think it’s true, right, that, you know, if you think of what the the projects on climate mitigation, like Sunday, maybe I have my economist hat on, but we would describe it as like providing a global public good, right. And that’s really hard. And, you know, what, you know, nation states are more used to providing like public good for their citizens, right, which you might think I’m bad at various types of adaptation, public adaptation expenditures. And I think, like thinking about what, you know, we definitely talked about possible models where you, I think, if you have that feedback in you could you would get this kind of bifurcation, potentially, where you end up in this like negative feedback loop? Where, what, you end up in a bad feedback loop, reinforcing feedback loop where climate damages, lessen the state capacity to undertake mitigation that leads to more climate change damages? I think, you know, I think it’s true, I think, you know, the working group and the effort that gave rise to this paper, we were interested in this question of tipping points in the social system, right? So we were looking, we were tending to, I think, look for examples of reinforcing feedback in the like, positive direction. And I think, definitely an next extension, for the model would be to look at some of these more, less good examples of tipping points. And I think that that is definitely one of them, this idea that you could get trapped in this, like, constant adaptation, constantly responding to climate change impacts, rather than lessening the ability to do these other types of changes. I think the other, you know, feedback that we don’t have in the middle right now, it’s that kind of negative public reaction to changing energy prices. And that’s, you know, we know that’s true. Like we’re seeing it right now. I think, and I would probably incorporate that as some type of, you know, reaction against rapid changes in energy, right? So you can, you can increase energy prices, but if you do it through a carbon tax, but if you do it very quickly, you have a negative response to that, right, that diminishes support for climate policy, and that would, you know, that would change that would definitely change our results. So I think some of that, you know, that’s all kind of work to be done in as we kind of flesh out some of the richness I think of what’s what’s in this type of model.
Michael Livermore 44:55
Yeah, great. Yeah, look forward to look forward to future future iterations and when The things that you mentioned there, which is another really interesting feature of this project. And something that we’ve kind of returned to on this podcast a few times in the past, which is, this is highly interdisciplinary work. And actually, in the paper, you even talk about, like, there was a four day interdisciplinary workshop. That’s where we kind of identified the feedbacks that we were interested in, which is very cool, I think, because that’s kind of how the real world works. You have these workshops, and you get ideas and you exchange, you exchange thoughts, and then that’s how you kind of, you know, build these things. So maybe you could just tell us a little bit about that. The workshop, the idea for the workshop, you know, the kinds of folks who were there and what the value was of that?
Frances Moore 45:43
Yeah, it’s Yeah, so it came out of this A into definitely working group funded by sync, socio environmental synthesis center, I want to say, in Annapolis, and it was Brian package, and Katie Lacasse. And Lou Gross had kind of who at some of the courses in the paper had been involved in a previous version of working group. And this was like the second iteration of it. And so we, it’s an interesting mixture of of disciplines, and several ecologists, there were some system dynamics specialists, this style of modeling is, you know, often called kind of systems dynamics, like focused on feedback loops and changes over time. And so that’s definitely, like, an important, like, piece of the modeling, and I think, and then kiddie of killer, like half of the psychologist. And, you know, like, there are disciplines missing from that. And so some of that was, like us reading a lot into into both literature’s and but it is, I think, it’s hard to get these things to always work well. And I think here, there was definitely a focus early on, on quantitative modeling. And so kind of everyone was like, on the same page, about that, and kind of willing to make the kind of necessary simplifications and so on, that come with trying to put very rich qualitative insight from some of these disciplines into a rather dry computational model in very, very, like simple functional forms. But a kind of people recognize that that was the end goal of this project, ultimate ultimately, and because of that, we could, you know, kind of came up with some some interesting work, I think, next, you know, we would like to have, you know, more disciplines in particularly recognizing using political science and law as being really critical to some of these, the the way in which, you know, collective action emerges from the space, I think, in general, this, this social ecology modeling, which is this, you know, that’s, there’s been a lot of that within ecology, right. So ecologists are used to thinking of how to species interact with their environment, and how to the environment that shaped the species evolution, and like, the extension of that, then to like, humans is a natural one. And so you’ve seen some of these types of type of modeling work in, in kind of coming out of ecologist and so I think that’s, you know, why you see, you know, that’s why we have, like, ecologist involved on this paper. But I think bringing in more of like, specialists within, within the social sciences that are interested in engaging in this type of work, it’s, I think it’ll like, you know, would be really valuable.
Michael Livermore 48:40
Yeah, no, it’s, I mean, it’s fantastic, though, what you’ve done so far, just to bring these disciplines together. And again, you know, as you noted, you know, at the end of the day, for an exercise, like this stuff has to get translated into quantitative terms that can be put into a model that can generate, that they can interact with each other and generate outcomes. And so, that can always be a challenge to integrate some of these more qualitative disciplines, folks can get uncomfortable with making assumptions about like, what the coefficient is going to be when you parameterize a model, but, but I do think that that is
Frances Moore 49:15
not just a coefficient, but I think sometimes people can get very hung up on the terminology and you can you get you get into debates about rather what I would call like semantic debates that are not particularly substantive. Because, you know, semantics are important in in some of these disciplines, but when you start translating these ideas into number of like, a lot of it, you know, really these these nuances, these distinctions start breaking down, and you have to be willing to like let go of some of that and kind of, you know, recognize that oh, what you call this and what I call this are really when we actually try and like put in into a model like that the kind of functioning of the same thing and we just have to like, live with that and like, like, let go of some of these. More semantic make distinctions. And that, you know, it takes a certain kind of flexibility of mindset, I think for for people to be able to do that.
Michael Livermore 50:07
Yeah, but that’s also useful intellectual exercise in its own is to, you know, when to kind of nail this and say, actually, you know, we’re talking about the same thing when it comes down to it. Yeah, you know, that actually takes a back us back, I think a little bit to that initial there that point that I made earlier about the different kind of philosophical underpinnings of these different approaches, because you mentioned, you know, kind of ecology and the way that, you know, we can we could think of, you know, ecosystems and species and ecosystems just kind of all interacting with each other within a single kind of model. And there’s no reason in principle not to think about, well, at least, in one worldview, there’s no reason in principle, not to just think of humans exactly the same way that we’re conditioned by our environment, we then interact with our environment have effects on the environment that feeds back to us. And it’s kind of a, you know, what you have is almost like a fully causal model of the human climate system. Now, again, you know, as you note, it’s not like, comprehensive and complete and whatever else, and you making a rough cut, and, and, you know, an attempt to include what you think are the important features. But, broadly speaking, the underlying idea is that, you know, we’re acted on by causal forces, we have characteristics that then, you know, can change over time or not. But you know, that we’re kind of embedded in this dynamic, essentially, that is kind of fully enclosed, from a causal perspective. Whereas under like the Northouse model, you know, what you might say, one way to interpret that is, we have a choice, you know, there’s no social decision maker in reality. But we ask this question, which is, if I were a social decision maker, what would be the right thing to do? It’s kind of a utilitarian worldview that says, Well, this is really what social decision makers are the people who are best positions to best position to make social policy ought to do because it maximizes, you know, social, social, welfare, social wellbeing. And then you could think of the the IPCC world as being a little bit more agnostic in terms of the ethical framework that it’s using, right? There’s not, it’s not clear that they’re trying to maximize social welfare, it’s not really clear what their utility function is exactly. But basically, they’re saying we have a choice. We can choose emissions pathway, A, B, C, or D, what kind of world do we want to live in? And we have to decide that collectively? I think it’s very interesting. So I guess I’ll just be curious about your thoughts. Is that something that you we that you all considered when thinking about the your model? And how it different from the other models? Or was this? You know, is this a little bit of a philosopher’s point? That wasn’t really front of mind?
Frances Moore 52:48
No, it’s definitely I mean, it’s definitely something I think your typology is exactly accurate there. And it’s definitely something that certainly I was thinking about. And in particular, it came up when I was kind of communicating about this paper, I was talking to people about it. And people would say, What do you mean about what we can do? And it’s like, well, it’s kind of not that type of model. Right? It’s very much a descriptive not a normative model, right? It’s kind of it’s telling you like, well, if this is, you know, the type of world we live in, and this is what you know, emissions are likely to be and if this is the type of world we live in, then this is what emissions are likely to be. And in that tentative, very, like the goal of the modeling exercise is understanding and descriptive, primarily, and not necessarily prescriptive or normative kind of in its intent. And that makes it different. I think, then some of these, you know, the goals of use of a modeling exercise, do you feel that role is kind of giving advice a to some imagined decision maker, but, you know, the problem is that like the the world, global decision maker kind of doesn’t exist for these complex, wicked problems, like climate change is one example. And I think, you know, I think it does, you know, in that sense, what this is doing, it’s pointing to the importance, like if you take the science of sustainability and the science of social ecological systems seriously, then the driving, like, determinant of how the natural systems evolve over the 21st century is going to be people, like people collective decisions, and you need like, you can’t just exclude that from your understanding of the system like you, you’re kind of like taking the the most important driver and you’re explicitly saying, Oh, no, we don’t do that. We don’t model that. And to me, that’s just very unsatisfying as as a scientific exercise. And so I think, I think there is echoes, I would say, there’s echoes here of what like Elinor Ostrom in the sense that, you know, she studied scientifically the emergence of like behaviors that you know, kind of leave collective decisions around multiple resource resource management. Right? And, you know, a lot of her work was looking at, you know, under what situations do you see this arise? And and what situations, do you not? And it was this descriptive exercise and she would very, she tend to be quite averse to thing, you know, like, oh, well, here’s what we can do to manage this type of resource that it was what we’ve tended not to be particularly prescriptive in that sense. And I think you can see this in the same vein in the sense of like, what we’re trying to do is we’re trying to understand and predict and project these the emergence of collective action around, you know, governance of various types of environmental commons, in order to better understand both the prophecies that give rise to that type of governance, as well as the behavior of the, you know, of what the trajectory of those systems will look like, over time.
Michael Livermore 55:51
Yeah, yeah, that’s really that’s interesting, an interesting connection to to Austin’s work. So that does make a lot of sense. One, one feedback that just just occurred to me that maybe you could include in in future iterations is the feedback effect of your model into the policy process, right? Is that it not now it’s out, it’s people can see it, and then you know, that, that if people change their behavior on the basis of your paper, that itself is a kind of feedback effect. Maybe a little hard to incorporate into the model, but, but kind of fun to to contemplate. So, so one, maybe final question for you is, again, with this predictive enter enterprise, and kind of with the state of modeling, obviously, you’re not saying we know what the world is going to look like, right? You’re saying, look, there’s some probability distributions, and we think these are some of the important features of the world that will bear on whether we find ourselves at, you know, two degrees, or three degrees, or three and a half degrees, by the centuries. And, and so, again, as someone who’s been in the weeds of the model, and seen them the rounds, and done the analysis, one of the things I would be very interested to hear from you is, you know, what are the things that we should be looking for over the next 10 years? Like, what are the features of the social world or the technological world, that, that we that we want to know about that, you know, if if x, if we observe x, then this should give us hope that we are going to stay within a reasonable temperature change? Or if we see y, then, you know, it’s time to move to Canada. You know, what, what are the things that we should be looking for? You know, is it the next midterm elections? Or is it you know, what, you know, is it like something, you know, in terms of polls, if polarization political polarization continues the same on the same track? Like, what are the things? Is it just public opinion? Yeah, what are the things that we should be looking for over the next five to 10 years, that will be a signal about what world we’re most likely to find ourselves in?
Frances Moore 57:56
Yeah, I think I’m probably going to reveal my economist tat, my economist background here, and I’d say, probably something along the lines of carbon pricing, because one of the common features a near term features of, you know, these walls that look more optimistic, is you see quite rapid increase in the stringency of climate policy where that’s measured in terms of some kind of average carbon pricing measure. And I think if you, you know, kind of over the next few years, if you know what we’re starting to see that like the Europeans, carbon prices going up rapidly. Same in California, like, and so and but it’s not just carbon pricing, right? It’s also to the extent we have more ambitious, you know, non pricing climate goals, like renewable portfolio standards, or other types of, say, efficiency regulations that are that are binding at affect cost, right, that kind of that’s kind of all rolled into that measure of the kind of equivalent the carbon tax equivalent. And so I think, if you, and this is globally, right, so I think in Americans tend to concentrate very much on like, what’s happening at the federal level in the US, but, you know, we should recognize that, you know, emissions in the US and, you know, no unrelated to what happens like everywhere else, because there are these spillover effects via via market, and technology, spill overs and things like that. And so, yeah, I would, I would definitely be keeping an eye on that over the next 10 or so years, I guess, this year, to see to what extent our model projections, kind of being borne out.
Michael Livermore 59:39
Yeah. Yeah. It’s really interesting that as a, in a way that we could probably just keep our eye on emissions, then is that, you know, under the more optimistic scenario, that’s
Frances Moore 59:47
a flow that has a slower response. Right. And that also that also depends more on the you have the question about what emissions technologies during the time, but I think you can really distinguish you know, Are you in this mostly this set of more positive tape, social political system wells or not? Based on what happened to the carbon price in the fairly near term?
Michael Livermore 1:00:11
Okay, well, I’ll be all the more reason for us to hope or Hey, as stringent carbon price not only will it actually generate the outcome, but it will predict that will be in a good world as well. So, okay, well, very good friend. Thanks so much for chatting with me today. This was a super fun and informative conversation.
Frances Moore 1:00:29
Thank you so much for the for the great questions.
Free Range Podcast 