Lars Peter Hansen on Uncertainties in the Age of Climate Change

(Intro Music Starts) Sam Hansen Hello, it is your host Sam Hansen and I am excited to welcome you back to Carry the Two, the podcast from the Institute for Mathematical and Statistical Innovation about how math and stats impacts the world around us. While we’re in between our more in-depth seasons, we like to bring you something a little different in mini-season format. And for this mini season, we are going to highlight some of the amazing researchers who have presented at IMSI over the past year. Our sixth, and final guest is Lars Peter Hansen My name is Lars Peter Hansen. Sam Hansen Lars is the 2013 recipient of the Nobel Memorial Prize in Economics and a Professor at the University of Chicago Lars Peter Hansen I have appointments at the Economics Department, the Booth School of Business, as well as the Statistics Department. Sam Hansen Lars joined us at IMSI for a workshop on Economic Impacts of Climate Change where he presented a talk titled Climate Change Uncertainty Impact Social Valuation and Policy? So, without further ado let’s get into my conversation with Lars Peter Hansen (Intro music ends) Sam Hansen When you're talking about designing policy, what are some of the trade-offs around policy design that have to do or are related to uncertainty? Lars Peter Hansen I think there are two important trade-offs that uncertainty puts on the table. The first one is the following. When we build mathematical models, we can use them in multiple ways. One way we might use them is the fact to, to allow us to make best guesses. What's going to happen in the future? As I change policy, what's my best guess? What's going to happen? The other way to use it is to say, well, what could be more extreme outcomes? An adverse outcome, for instance. If I, what's the possibility in terms of things that might happen and things I might want to be worried about? Both those uses of models are very important and can be very valuable. There's an interesting trade-off between how much weight you put on best guesses versus how much weight you put on more extreme outcomes, especially the, you know, especially the adverse ones. If you spend all your time on best guesses, there may be a non-trivial possibility of something bad happening that you've ignored. If you only care about bad outcomes, then, you know, you may just give up and not get up in the morning because things could be so terrible. Really, in decision-making under uncertainty, there's a place in between that, that you want to be. So that's one of the trade-offs. The other one that I think is very important is: do we want to act now or do we want to wait until we get more information in the future? There's always a temptation to say, well, since we're going to figure more stuff out in the future, let's just wait. But it may be very, very costly to wait until the future. It may be more prudent to act now under the possibility of particular outcomes happening instead of waiting until you're completely confident that such outcomes might actually, will indeed happen. Sam Hansen And so if we're talking about policy around climate change and global temperatures and things like that, what are some of the uncertainties with the economic impacts of that, that you would study? Lars Peter Hansen So the ones that we study, and these are not all of them, are four. One is the usual one that economists study about: if I make certain investments today, they're going to have longer term uncertain payoffs, successes. And so economists have studied this one in terms of investment problems for many decades now. It's kind of fundamental health economic dynamics. So that one's there. Ones that become a little bit more unique to climate change would be imagine that we emit carbon in the atmosphere today that's going to impact, say, temperature or more generally the climate system in the future. What are those kind of longer-term impacts on climate change of carbon emissions today? The third one has to do with if we have climate change in the future, what impact is that going to really have on economic opportunities? Of course, economies have historically adapted to different type of environments and the like. There'll be some adaptation that, that might take place. There may be some rearrangement of the productive capacity of the economies and the like. At the end of the day, what are the economic consequences of this and how will economies respond to them? This comes under the heading of what environmental economists would call damages. The final one has to do with technological progress designed towards helping us with climate change. So as we get, as we engage in research and development today for the discovery of new technologies, technologies that might remove the need of fossil fuels. Those are, there's different possibilities on the table. We're not sure about their payoffs, when they will pay off, and exactly how successful they will be. But on the other hand, it makes sense for society making some investments in these type of technology changes. So what will a lot of a progress be in the future that's relevant to addressing climate change? Sam Hansen How did y'all go about starting to study? Like what was your approach for studying these uncertainties? Lars Peter Hansen Kind of in a nutshell, what we do is we start off and come up with baseline type specifications. These specifications include things like random shocks. So there'll be probabilistic specifications. We have dynamic stochastic models, which we use to analyze things. So we start off with some baseline type specification. And many analyses start there and end there. For us, then, we need to – so here we need to have inputs from different components, which I described. And then they're going to interact in the context of the model itself as we do, as we start solving and analyzing ramifications for different economic policies. So for us, that's the starting point and not the ending point. We also then want to start asking, well, these baseline probabilistic specifications are, in some sense, guesses. We're not completely sure they're right. There's often simplifications made to kind of simplify the numerical analyses as well. What are the consequences of us not being quite right there? What are the consequences of where we're not 100% sure that that's the right specification? How do we then look at the ramifications of that? And if things could be off, where are the sources of it being off that really matter for the decision problem, for the policy design? Not all mistakes are going to be, or not all kind of changes here are going to be equally impactful in terms of, in terms of the design of a prudent economic policy. So part of what we're about is to kind of at the same time be building numerical techniques that help us understand where the uncertainties really matter. Once we identify where, where they really matter, then that can open the door to further scientific investigation, seeking out better information along some dimensions, or investing, say, in knowledge accumulation going forward. Sam Hansen And if I understood your talk properly, I believe that you started to then use an area called decision theory to dig into some of this. So how can decision theory or a decision problem help you determine which of these uncertainties or where these uncertainties are most consequential? Lars Peter Hansen The uncertainty potentially for a model like this can be very high dimensional. I've already outlined four different channels the uncertainty could affect things. Each one of those could have a certain type of richness attached to it. And so it's opening the door to different places in which there might be ambiguities in the specification. There might be potential concerns about misspecification. The decision problem, what he put on the table, then, allows us to say, well, among all these high-dimensional uncertainties, which ones really matter? So we use the decision problem to figure out, to sort through these higher-dimensional components of uncertainty, to figure out the ones that are most impactful for the problem at hand. Without a concrete decision problem, that would be to just be left with high-dimensional uncertainty, and that would be it. But for us, we need to take uncertainty qualification beyond just the characterization of the uncertainties, but to ask the so what's of the uncertainties. And that's where this notion of a decision problem comes into play. Sam Hansen So what was the decision problem that you used when looking at the climate change uncertainties? Lars Peter Hansen We took a highly, what I would call a highly stylized initial approach, that this is not the end game, this is the beginning game in many respects. We consider hypothetical, this hypothetical, which we call social planner: this person is saying well I'm going to look at the global system and I'm going to try to figure out what would be the most prudent thing to be doing. Now of course actual policy making is far more complex so there's multiple players on the table the players may have different incentives different objectives and the like but for a starting point we take this kind of what we call this fictitious social planner approach and then we analyze the various different sources from the perspective of that. So we're going for what would be the ultimate kind of well-designed climate policy. And then we can start adding in more complexities to the policymaking process as well, which is indeed very important, but we're just taking this initial step. (Ad music starts) Sam Hansen If you're getting a lot out of the important research shared on this show, there's another University of Chicago podcast network show you should check out. It's called Not Another Politics Podcast. Not Another Politics podcast provides a fresh perspective on the biggest political stories, not through opinions and anecdotes, but through rigorous scholarship, massive data sets, and a deep knowledge of theory. If you want to understand the political science behind the political headlines, then listen to Not Another Politics podcast, part of the University of Chicago Podcast Network. 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So we can't just look at historical evidence and say, well, here's what's going to happen. These so-called subjective components to model building in this case, and the damages are a key place where that's the case. So there's been lots of people conjecturing that damage uncertainty is a big deal, and we would agree on that. We were looking at a particular type of technological, progress, change. That is kind of the big project of change. You know, the kind of climate analog to building atomic weapons during the Manhattan Project or the climate change counterpart to putting people, astronauts, on the moon or the like, ones that, you know, require some type of very big investment. One can think about the type of investment could be a nuclear fusion technology, which is highly uncertain, but has a promise that if it does get developed in an economically viable way, could really have major impact in terms of addressing climate change. So we were looking at these big project type research and developments there. And it turns out that that kind of dominated our uncertainty. That's the one that really mattered the most in terms of our calculations. So that's the one thing. So we put in these different four channels and that's the channel that kind of mattered the most with the damages coming in next, as kind of the second most. And then the way we do this, roughly speaking, is we imagine activating all the channels simultaneously and then activating one at a time and see which ones, which form of uncertainty gets as close as to the ones where we're activating all simultaneously. In this case, this research and development type uncertainty became the important one. So that showed up. Now, there's another aspect of our, of this calculation that initially surprised us, and we now have a much better understanding for it as to why. Usually, when people think about investment problems under uncertainty with multiple choice of investment, one thinks about, well, you make society more averse. OK? So part of this decision problem is you have to decide how averse society should be to these uncertainties. That's a statement of societal preferences. So we can hypothetically ask if we make society a little bit more averse, what's going to happen to these social investments and things like research and development? And so for standard investment problems that people analyze in finance, it will often be the case that if you add, if you increase this aversion to uncertainty, you want to do less of it because you're less sure of what, uh, the prospects for the technology and those sort of kind of shift towards ones in which you're more confident. In this case, we were finding the opposite. We were finding that even though when he made our decision maker more averse to this uncertainty, less confident in these baseline specifications, when he eliminated that confidence, we actually, the policy was to be more proactive, not more passive. And so that That became a very intriguing part of our finding and that we've spent, we're spending time trying to contrast or trying to explain exactly why that's the case. Sam Hansen You said that you do understand that a little bit more now. So can you tell us a little bit about what you have found since about this aversion? Lars Peter Hansen Sure. So there's two offsetting forces. One is the one that I just described that would show up in a lot of kind of standard investment problems under certainty. And as you make the decision-maker more adverse, you might well do less of it and shift towards investments that there's more confidence in. But here, this problem, what makes it different than a lot of more standard problems coming out of finance, is the payoff itself. So we have to think about how about a success? How about an R&D success? An R&D success itself, we have to compute what that ramification as model solution. So we're actually figuring out how important is it to society to have the success or what's the value to it. And the relative value to that, that success, if you make that person more averse, actually is higher relative to not having the success. So what's different from a standard investment problem is that when we're changing this aversion, we're also changing the consequences of a success here. So if you make this discovery, you've eliminated a big chunk of uncertainty going forward, and that's a big winner. And the more averse you are to uncertainty, the bigger that win is. So there's this first channel, which, well, I'm not quite sure when this is going to pay off, I'm not very confident in that. That makes you want to do less. But then the consequences of a success make you want to do more. And so we show that quantitatively the second one dominates. Sam Hansen That's fascinating. And so once you've done all of these analyses, once you've completed these studies, how would you then go talking to people who are the policymakers, the people who are actually implementing these things? How would you approach them and talk about how you understand these uncertainties in a way to help them make the policy more effective? Lars Peter Hansen Yeah, that's a good question. So my own direct communication with policymakers has been more to, actually, central bankers than others, although there's been a little bit of connections elsewhere. My view on that is the following. To go to the actual final decision maker, they're spending all their time trying to sell things to public and the like, and the people you can have the best chance of influencing are the policy advisors. And they're the people who would have the patience and maybe the background to understand how these arguments really work. And then let that person translate or figure out the way to sell it to the out-front person trying to market the policies to society. So I think our best hope is to be able to influence the advisors to the different policymakers. And for various projects, I just described one of the projects which we've been doing. We've been doing other work on the Amazon rainforest, that my colleagues have been spending time talking to a variety of policymakers about. You can have successes in talking to the advisors, especially since some of them have some very sharp and very sensible advisors. Sam Hansen And so I have one last question for you, and that is: how was it to be a part of the workshop at IMSI? Was it a good experience? Have you had, did you were able to make connections? Did anything positive come out of it? Lars Peter Hansen So the thing that was advantageous there was the following. I find workshops of this type to be valuable when we bring people in from applied math and from people that kind of use applied math to actually solve substantive problems. And to have those conversations go back and forth. And so the presentations themselves were of some value, but of maybe just as much value are the more informal conversations that evolve afterwards. They evolve over coffee. They evolve over subsequent meetings. They open up dialogues that might not otherwise be in. They nurture those type of communications. And I think to address problems like, say, climate change, it becomes very important to be drawing on expertise across the board, including kind of mathematical and technical expertise. You know, coming out of IMSI, we're now, like, collaborating with people that are better, you know, even more expertise than we have in terms of computations. We're having some conceptual discussions with other applied mathematicians and the like. And so it helps us understand what the frontier of possibilities are, are there. Because, you know, it's very hard for me to keep track of all this on my own. Having these conversations, though, and opening the door to collaborations can be very, very valuable. So that's what I see as the big game, this opportunity for conversations cross disciplinary in nature. Sam Hansen Lars, thank you so much for giving me your time today. Lars Peter Hansen Sure. I hope this is what you're looking for. (Outro music starts) SH: And that is it for this mini-season of Carry the Two. We will be back soon with our next in-depth season where we will be digging into the mathematics and statistics of emerging technologies. As always, don’t forget to check out our show notes in the podcast description for more about Lars’s research and to watch his talk. 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