 Hi, everyone, we'll be convening for the next session right now. And I just wanted to give a brief introduction as we convene for this session, which is entitled public and financial sector climate risks and responses and their macroeconomic implications. The reason that we set up this section after the one before is just the recognition that the climate crisis is already affecting many aspects of our economy. And one way we're seeing this happen is, for example, in the way insurance markets are reacting to extreme climate risks. We've seen very recently two major insurance companies say they will not offer any new policies in California because of the rise in catastrophic wildfire risk specifically. This insurance reaction is kind of a canary in the coal mine because these risks are actually there in many places in our economy. The market for the large part is not fully capturing the signal. It is still flying under the radar. But the physical risk from the climate science perspective is very, very clear. So, for example, on wildfires, the signal around increasing wildfire risk in the Western United States has been clear for at least a decade, if not longer. Of course, that science is getting ever more dire, but the signal was already there. It was just not being translated into the market yet. And that is a really cautionary tale for us because this kind of a risk flying under the radar exists in many places in our economy and they might individually look like micro risk to specific sectors, but they will add up to a substantial risk to the stability of our economy overall. And just as a few examples, we've got trillions of dollars of real estate all around our nation that are in areas that are flood prone and wildfire prone. Those risks are increasing substantially because of human caused climate change and they're accelerating in many cases, like in the case of sea level rise. We have extreme precipitation events that are also making flooding worse, hotter, drier conditions, fueling catastrophic wildfire seasons that in some places are now becoming year round. We also have a substantial risk to public health from a range of climate impacts, whether it's the smoke from wildfires or extreme heat, which takes a terrible toll, mortality and morbidity, especially on people who have to work outdoors. So there are real labor implications of this and there are huge equity implications of these climate risks as well, which often when you aggregate the impacts and look at it from a macroeconomic perspective, you can sometimes lose the fact that there are big parts of our population that are especially exposed to these risks because of long standing socioeconomic and racial disparities in our country. So in this section here, what we wanted to do was highlight some of these risks with the idea that we can start to appreciate that while they might look like individual sectoral risks right now, we have to get out ahead and make sure that we're preparing because this is coming for us in a much larger way. And specifically, one of the things that we want to point out in this section is for the large part, our response has been a disaster response, a reactive response rather than a proactive recognition that we have to be thinking about climate resilience in a more holistic way because it is going to affect so many people and so many parts of our country. So we have three excellent panelists today and we're going to start with Laura Backenson, who's an associate professor at the University of Arizona School of Government and Public Policy. She utilizes applied microeconomic and econometric techniques to study the economics of natural disasters, identifying current and future risks and evidence of adaptation to damages and fatalities across the globe. Laura. Thank you so much. It's wonderful to be here and it's been a wonderful discussion thus far. So I'd like to review three of my own papers, just as kind of examples of this, the spirit of this work and the questions that are being asked. So the next slide, please. So first, and if you'll indulge me a little outside the scope of particularly this panel, but I think very relevant for the conversations we've been having yesterday and today, I the the importance really of kind of bridging this micro macro gap or how can we take the rich results, for example, from the third panel yesterday and better incorporate them into macroeconomic models. So there is good work doing this, but one one of my own papers looking at this is joint with Lent Baraj at ETH Zurich. And we were looking at we were motivated by kind of this rich theoretically, sorry, rich empirical literature and examining the impact of natural disasters and climate risks on economic growth and noting that there are sometimes were divergent findings or findings in tension with each other. And also there could sometimes be more limited connection with macroeconomic theory and limited integration in macro climate economy models. So we thought there was a lot of important opportunity both to inform these models and also increase the richness of the climate economy models as well. So one of the insights that we followed was instead of looking at the impact of natural disasters, so we take the case of tropical cyclones and look at the impact of that on growth and use that to protect climate change, we instead use empirical evidence of the the modeling the structural determinants of growth. We could then use kind of the rich portfolio of data available and directly insert these findings into a stochastic endogenous growth cyclone climate economy model, which is exactly what we do. We have a modified version of work from Tom Krebs incorporating the risks of cyclones. And one of the one of the benefits of this is that we could then kind of directly import these kind of rich empirical findings into the model and find what difference that makes. So we actually find that it it can help to inform both literatures. Having a structural lens for the micro empirical more reduced form literature can help inform empirical specification and interpretation. So for example, seemingly innocuous decisions and modeling, for example, operationalizing a climate risk, so tropical cyclones by, you know, the damages they cause versus the wind speed. This actually maybe would be identifying or track back to different parts of this underlying growth equation and therefore tensions and findings across empirical literature may not be so much in tension. And in fact, just just looking at different parts of this overall equation. We also note that there are sometimes that one of the benefits for macrostructural literature is again, we can more directly integrate these very careful, thoughtful, empirically grounded findings and bring that richness into the macro literature to be able to, you know, make these findings and models more more connected with with the world. Next slide, please. So more at in light of what we were thinking about for today's panel, there's an important question as to what extent climate risks are impacting or occurring in financial markets. So in current work with one fan and Russell Wong at the Richmond Fed, we wanted to look specifically at the impact of climate risk in the collateralized debt market. And to do so, we build a new model, extension of a model to look at debt in with under belief heterogeneity. So an important area, and I think this was picked up in the previous panel as well, is is heterogeneity or disagreement in beliefs surrounding climate change? We see this very evident in the United States as well. Typical collateralized that market work by ginocopolis, some sec, etc. Commonly find that optimists are more likely to pay more for the asset, a risky asset and also more likely to leverage. We extend the traditional model into an infinite time horizon, which allows for heterogeneity and maturity of the debt contracts and actually find that this reverses this finding. And in fact, pessimists, we find to be theoretically and also empirically using the case of seal of rise using a large scale data set from the for more than a decade of home sales along the eastern seaboard in the United States. We find pessimists actually to be more likely to leverage and for longer maturity debt contracts. Why is this the intuition being now while nobody would hope to default on a mortgage contract, the default channel actually theoretically allows for some implicit insurance and can act potentially as an insurance to potentially incomplete insurance markets running some of these climate risks. So as we know in flood for flood risk, this is primarily overwhelmingly public insurance market through the national federal transfer market in the in the case of the United States. But there can be limits to there are limits to coverage of about two hundred fifty thousand dollars per property. So this could lead implicitly to some supply side constraints. Policies are typically only for a year or in a few cases, just a few years, which does wouldn't help with these long term climate risks that may be on decadent old timescales. And so also important is highlighting that better climate information, people being attentive to climate risk may not necessarily mean that potential concentration of climate risk and financial markets will be solved. So in this case, with additional attention to climate risk, we may actually anticipate more more individuals taking out more just potentially there also is a critical role of policy in this story. We find that this this channel with pessimists leveraging more one of the questions as everybody knows that these these assets are at risk. Why not just price that in? And we find in actually building on previous work by Aminos on that con and others, the important role of government sponsored enterprises currently through policy, including some some policy constraints. These types of climbers aren't currently priced into their pricing of securitization of these mortgage portfolios. Therefore, banks maybe could potentially be theoretically fully attentive to these risks, but knowing that they may be able to securitize and pass on riskier loans to, for example, GSEs, then they could act as if they are less concerned about these climate risks. And so we find, empirically, that this results this kind of pessimistic channel is is almost entirely found within the conforming loan segment that could be securitized to the GSEs. So I think this is just a highlight as to the role of climate risk in the financial market. I think this is a really important area for continued work, as there are a lot of unanswered questions and also the interaction between public policy and collateral asset markets and other financial markets. And importantly, also the role of believe heterogeneity and how the role of climate information is certainly a critical and necessary component in solving some of these risks, but potentially insufficient, especially if coupled with other policies as well. Final slide, please. And so I'll dig a little bit more into public insurance, because I think that this is a really or insurance around public sorry, climate risks in general. In the case of flood insurance, of course, this is a primarily public insurance product, but we know that across other climate risks, the private market is is very active. So in a paper with La La Ma, we looked at sorting over flood risk. So I know the issue of migration had come up. We look just within metropolitan area sorting here. But the idea that people may move heterogeneously. And in fact, we find unlike, you know, common thoughts that high flood risk areas will be primarily white or high income, which we do find consistent with our case in South Florida. For coastal flood risk inland flood risk, we find to be a very different story where low income, black and Hispanic residents are more likely to move into harm's way in part because prices are lower, all else equal. We then can use this structural sorting model to examine counterfactual price reforms of a national flood insurance program. These are not the current risk rating 2.0 reforms, but there could be important parallels and we find that since there is this heterogeneous sorting, certain groups may be less likely to move out of harm's way, given the increase in prices. So in our predicted counterfactual results, we find again, these low income, black and Hispanic residents are would be more likely to bear the costs of these costly price reforms. Again, there's many reasons why we may want to be undertaking the price reforms, but an important flag that there could be unintended consequences that could have disproportionate burden on more vulnerable groups that are already in harm's way. Just a last final thought, as I know I'm almost out of time, I think this is really highlighting conversations we've already been having about potential market incompleteness and insurance markets and the role of state run flood insurance markets and public insurance markets that will be kind of stepping in to take take on the role when the private market may be shying away from some of these areas. So I'll stop there, but thank you. Look forward to the discussion. Thank you very much, Laura. The next we have up is Daryl Fairweather. She is the chief economist of Redfin, the real estate company where she leads economic research about the housing market. Hi, everyone. Good to see you all. I am in Wisconsin right now, and there is a moderate amount of wildfire smoke lingering above me. So it's a great day to talk about climate change and the impacts on how we live. I'm the chief economist at Redfin. Like like you said, I'm I lead the economic research team for the benefit of our executives, our agents, and also our customers. Next slide. So I'm going to be talking a bit about the research that we've done on climate change. We got climate change data onto our website and app late 2020. We did an experiment with it and then it went well. And we decided to launch all kinds of climate change measures down to the individual home level. So from First Street Foundation and from Climate Check, we have data on all different kinds of climate risks. And if you could look up your home, you can see exactly what your individual projected risk is. Next slide. We did some research into where Americans are building homes based on this data that we have, and we found that increasingly homes are getting built in riskier areas, especially for fire risk. So in the first half of the 20th century, only 14 percent of homes were being built in fire risky areas. And now that is up to 55 percent. We are certainly making climate change worse in terms of the impact on housing just in terms of our building patterns. Next slide. And this is happening because of encroachment into fire risky areas. So you can see here, or not fire risk areas, climate risk areas. This is a map for drought. There are other maps that kind of show the same pattern. But in Phoenix in particular, you can see that the building has happened in places with higher drought risk. And recently, Phoenix even announced that they were going to start limiting building because of the strain on water that building is having. But there are other things that draw on water. It's obviously not just housing, they're agricultural uses of water, but they are stepping forward with limiting housing. Next slide. So on top of the fact that people are building homes in places that are risky, people are moving to those homes. I mean, that makes sense where there is supply, demand will usually be there too. And you can see that people are are moving to the places with some of the highest climate risks in Florida, in particular. You know, there's all kinds of risks, heat, flood, storm. And Florida has been one of the top migration destinations for home buyers. Right now, we look at where people are moving and when they're leaving their their metro area based on redfin data, we have on where people are located based on their IP address. And we've identified people who are searching in one metro area and looking to move to another. And in that data, five out of the top metros that people are moving to when they're moving out of state are located in Florida. And then you can see other places, too, that kind of fit this pattern, like inland California and then people are leaving some of the less risky places, like the Midwest and the Northeast. All right, next slide. OK, so I'm going to talk about an experiment that we did when we first launched climate change data on the Redfin website. So on the Redfin website, you can find all kinds of information about a home, pictures, the specifications, number of bedrooms, walkability is a data that you've had for a long time, school quality. And we put this down on the site because we think when people are looking for a home, they're going to want to know also about the neighborhood and also, you know, things about the individual home. And we have limited real estate per se when it comes to what we put on the site. So we weren't positive. We wanted to add climate change data. We weren't sure if it was going to be something useful to our customers. So we first did it. We did a three month long experiment where we only showed flood risk data to half of our customers. Our next slide. So here is the control view, the treatment view and expanded treatment view. This is on the mobile app. You can see in the control view, there was no there was no tab for flood risk. But we added the tab for flood risk, and then you can click in and see all this different information about flood risk for each individual home. So it will look different for every single property. Flood risk is one of those things where at the top of the hill, you have less risk than if you're at the bottom of the hill. So it does vary quite a bit. And yes, we added the site with this experiment lasting three months. Next slide. So what we found was that Redfin users who viewed homes with severe or extremely risky flood risk prior to the Redfin experiment ended up bidding on homes with 54 percent risk. It was like a one to 10 scale after gaining access to the risk data. So extremely risky or severely risky, I think was like seven and above. And then they got homes, ended up with homes about half that risk compared to people who were not exposed to the treatment at all. Redfin users and risky places like Cape Corral, Florida, Houston and Baton Rouge were most likely to click in and see the flood risk data. Makes sense. They're probably already somewhat knowledgeable about flood risk and would be interested in learning more. So one conclusion from this research is that, you know, if this were to there's some kind of unpriced value of having a less risky home. And that's not priced in. So over time, we will probably see home values in places with high risk, not appreciate as much as places with low risk. Next slide. This impact and fight over time. So you can see this is weeks since the user entered the experiment before no effect afterwards, a pretty monotonic decline in terms of the the kinds of homes people were searching for with their flood risk. So at first, not much of an effect. But at the end of the experiment, a 25 percent decline overall in terms of the homes people searched for, we had two different outcome variables. We had the types of homes people search for just in terms of what they did on the app on the website. But because we are also a brokerage and we have agents that work with clients, we saw all the way through for a smaller share of the users. So like users, a lot of people on the website, not many of them actually buy homes. Smaller share than actually buy homes with rent fined up for the ones that did. We were able to see the offer effect as well. So that's next slide, I believe. Oh, wait, actually, I already addressed that. But anyway, the offer result was that people built been on homes at the back half as much risk if they start off with severe or extreme risk. Sorry, previous slide. This is just another result. This is from a survey. So already out of home buyers, home owners, 58 percent of them say they've spent money to protect their homes from climate threats. Right now, it's about a third of home are saying that home owners saying they've spent five thousand dollars or more to make their home more resilient to climate risk. I mean, that could be something simple like upgrading a roof or doing some landscaping to have water flow away from the home. But already home owners say that they're kind of there, they've had to make some improvements because of the changes they've seen in their environment. This is survey data, but it's interesting. Extreme temperatures are the most common climate risk. The homeowners protect against air conditioning. It's obviously a good way to do that or insulation and then followed by flooding in hurricanes and 36 percent of home owners say they have an insurance policy covering flooding, which was the highest share. Next slide. OK, so I'll talk a little bit about the policy implications. Next slide. As discussed previously by Laura, it is most there's there's inequality in terms of who gets impacted by climate change and how able people are to respond. Well, the people in corporations are probably best able to protect themselves and their investments against climate change. The local and federal governments, they may also have an incentive to protect their most valuable assets, whether that's company like company buildings or high, high worth real estate. And then there's a question of who pays the damage from climate change. You know, a polity felt by everyone, but the magnitudes will not be equal. Some lower income people tend to live in places with higher risks. There's also historical inequality with redlining where redline neighborhoods, which only black and brown people were allowed to buy homes in or not were allowed to, but they ended up buying homes and tend to have higher flood risks. And that's still where black and brown communities live. So that historical racist policy still might have some impact today on who gets hurt the most by climate change. And then there's a question of who is allowed to stay and who is forced to move if governments invest in, say, Hamptons, but they're not going to invest in Alabama, then, you know, there's going to be some inequality in terms of who gets the investment to stay and make the communities more resilient and who gets relocated. But a lot of marginal costs, marginal benefit, social planner problems to think about. Oh, sorry. One more slide. I forgot. Forty three seconds. So what we can do is we can limit building in high risk places. This can be done by paying communities not to rebuild and to use the and to maybe have that building go somewhere else to discourage movement into these high risk areas. We can eliminate single family zoning in low risk areas and other restrictive practices that limit dense housing. And we can also raise awareness about risk. I mean, the experiment pretty much showed that if you show people information about climate risk, they do respond to it. So it seems like we should be getting the word out and increasing the salience of that information and doing it at the moment that someone is in the process of buying a home is probably a good way to go about it. All right, that's it. Thank you so much and feel free to reach out with questions. My co-author on that paper, Robin Metcalf, will be presenting it at the Summer Institute for NBER so you can see the full paper there. Thank you so much, Daryl. Our next speaker is Yanjo and Penny Liao. She is an economist and a fellow at the Resources for the Future. And her work focuses on issues of natural disaster risk management and climate adaptation. She focuses on the impacts of disasters on government budgets, how disaster insurance interacts with the housing and mortgage sector, as well as the economic and fiscal impacts of adaptation policies on local communities. Everyone, thank you so much. Am I supposed to see a countdown clock somewhere? Oh, yeah, I think. Hi, everyone. I am Penny Liao from Resources for the Future. My remarks today will be focused on the implications of physical climate risk on local government finance. Next, I want to focus on local government because while climate change is a global problem, the physical risks are highly localized. The impact of disasters related to climate and the decision to respond and adapt to disaster risk and climate risks are often made at the local level and exclusively depend on local government capacity. So when we think about the macroeconomic impacts of physical climate risk, it's important to understand how different localities are impacted by them and how they're dealing with them. So in this remark, I'm going to first talk about the multiple physical stress pathways that disaster risk can put on local government. And then I will talk about the attributionary issues. Then I will talk about the potential prices, which is overvaluation of housing in rich areas and insurance issues, which have been touched on summarizing nicely in the previous two remarks. But I will talk about them in the context of local government finance. Next slide. So climate related disasters can affect local government finance in a multitude of pathways. And in this diagram, I try to summarize some existing findings on these pathways, including some of my papers looking at how wildfires, hurricanes, floods and storms affect various different components in local government budgets. In general, we find that disasters make balancing the budget more difficult for local governments. This is primarily because of the need to increase spending on disaster recovery and adaptation, for example, after California municipalities are hit by a major welfare event, we find that they on average increase spending in community development by 40 percent. And there are also very large increases in public safety, transportation and disaster preparedness. On the other hand, revenues do not tend to keep up. And rather, they tend to decrease after disaster. Lastic tons of disaster damage on properties reduce the community's tech space in the short run. And if people respond to disasters or disaster risks by migrating out of the community, then it would lead to a long run erosion of the property and sales tech space of the local government. Two additional funding mechanisms are important. Sorry, still that on that slide. Yes, thanks. Two additional funding mechanisms are important when local governments are dealing with budgetary shortfalls from a disaster or when they want to invest in a major adaptation project and don't have the cash. And so these are summarized in the white boxes. The first is municipal funds. The ability to borrow at a low cost is important for local governments to move over any short run to the deficit. However, research has shown that disasters tend to lower political bond ratings for those communities that are hit and as increased borrowing costs, and so it could cause liquidity issues going forward. The second funding mechanism is intergovernmental transfers. These mainly take the form of, you know, a wide variety of disaster assistance programs, disaster aid programs by the federal government. And we find that disaster increases intergovernmental transfers to local governments, which can be very helpful for them to fund some of the recovery needs. However, these transfers also represent a form of processization from low risk to high risk areas and and they can raise equity concerns. Next week. And here I want to take a more systematic look at the attributional issues. It turns out that the average budgetary change that I just described last pretty important heterogeneity across communities in high income counties. We see that there is a substantial increase in spending following disasters. But in low income counties, we are not seeing much change. And this could suggest that low income counties are either not able to spend that much on disaster recovery or they're cutting down on other services. And when we look at revenues, we find that high income counties are more able to raise revenues of fund spending, their tax revenues actually increase and they get more intergovernmental transfers. And so overall, we also see that high income counties that actually have some moderate decrease various low income counties are borrowing more. One likely reason for these differences is that low income counties are less able to absorb the disaster damage as they don't have the same kind of financial buffer, either the local government or individuals. They might not have the same ability to raise additional funds because of the underlying economy or the market is less robust. Since we see a difference in intergovernmental transfers, there might also be some institutional factors at play. Some recent studies have suggested that disaster aid programs or disaster declarations are set up in a way that might favor a wealthier community. Because of these differences in responses, in the coming years, we might see divergent interest rates for communities with different capacities. This can exacerbate the existing divide between high and low income communities that can also have implications in terms of the spatial distribution of population and production. As you can imagine, that the more robust higher income communities might stay in place and continue to grow. And the lower income communities might be care raised in condition with more outmigration. Next slide. Next, I want to switch here and talk about potential surprises that are concerning. As the previous two remarks mentioned, a lot of the properties with risk are potentially overvalued because of various mechanisms, social laws, lack of information, socialization of disaster costs, subsidized for insurance, etc. And so in the recent application, we fontified the overvaluation across the US county. And now we try to think about what it means for local public finance. And in this, and you can imagine that when these kind of overvaluations get corrected, it could have major implications, particularly for those local governments that rely heavily on property tax revenues. And so in this map, the darker the state of yellow, the more dependent that county is on property tax revenue and the darker the state of purple, the more overvaluation there is in that county. And so these darkest areas, which we outlined in red, are counties that are most overvaluations. And if the overvaluation gets corrected, they might face pretty acute decrease in revenues and might have to come up with alternative ways of funding services that they provide. Next, and then insurance availability and affordability issues are also writing. As we know, insurance is a critical source of funding for homeowners to rebuild after a disaster. We know that wildfires is more 2015 and we see that actually wildfires are not impacting the property tax revenues in California that much. And one of the major reasons to see that at that time, wildfire damage is covered by regular homeowners insurance and the coverage rate is really high. And so homeowners have sufficient resources to rebuild. However, this situation is changing as we know. And in this map, it's not actually comes from an issue briefly put out last year. And it shows you that some of the codes that are at the highest risk at wildfires, the insurer in this case, in our renewal rates can go to 20 to 30 percent. And it's probably increasing over time. And we see the same kind of story in Florida, Louisiana, Texas. And it and this trend could exacerbate the disaster insurance coverage gap, which means that a lot of more and more homeowners might not have sufficient resources to rebuild, which might intensify the stress on local governments because the impact on property tax base after a disaster might be larger. And with that, I'm going to stop. Thank you very much. Thank you so much, Benny. And we have about 20 minutes for some open discussion and questions and answers here. So folks, please do use the raise hand function for those in the room and online if you have a question that you would like to ask. And thank you so much to the speakers. So please stay online for the Q&A now. Bridget, is that something that you'll drop in here? OK, great. And while we're waiting for questions to come in on the online format, I did have a question for all of you from different perspectives. You're all highlighting a risk that is in some cases already here, already starting to see the leading edge of it. But clearly a big chunk of the risk still not being priced into the market. It also feels like a nationwide risk in many cases. It's not just isolated in certain places because of all the different climate risks. So coming back to the theme of this workshop, which is to make the connection with the macroeconomic risk, how do you all see these threats flowing out to the macroeconomy? Because it's obviously not just about individual homes. As you've said, it's the property tax base. It's a mortgage market. It's all of our retirement portfolios that might have real estate in it. Budgets, local and national government budgets, insurance. So any big pictures, all it's about how we can start to think about it from a macroeconomic perspective. I can speak to real estate just because in housing, that's a really big part of the economy. We're already seeing it show up in the housing market when it comes to insurers pulling out of California. I understand that's partially because California is limiting the ability of those insurers to price and risk. So there's a bit of a market mismanagement there. But I think it goes to show that there are things that are keeping the true risk from being felt by homeowners at this point and that's only going to last so long because eventually insurers will put their foot down and then after that happens, you can't get insurance. You can't buy a home with a mortgage. So in housing, it's hard to say how big the effects are exactly. But they're probably going to be quite large in terms of people having to spend more insurance, their water bill, renovating their homes or having to relocate. All those things are expensive. And it's coming at a time when we already have housing shortage. I think Freddie Mac is estimated were about four million housing units short. We're probably shorter if you account for the damage of climate change. So I think there's a big reason to build more, especially in places that are naturally resilient to climate change. Yeah, no, I think that's really the big question. And I think that's really the frontier of a lot of research right now, seeing how these kind of local, regional, sectoral risks may scale up. I think there's there's a few pieces. First of all, just observing, quantifying, putting some numbers, you know, being attentive to where these risks are found and how they're starting to interact. I think that's a key piece in order to be able to very much in the spirit of this these discussions, how can we then incorporate them into broader macroeconomic models? We know there are many to look at some of these different mechanisms and channels to what extent this will change, you know, a firm or individual decision making and where to live or what to invest in, how much to save. These could have reverberations, of course, for the broader economy. I think there's increasing attention on kind of climate stress testing in some of these financial areas in order to see because I think there's kind of two key areas here. One is the long run climate risk and how that's being incorporated, which can have very different dynamics than individual climate events. Both are quite important in but get different types of studies, but understanding how these tail events could trigger, you know, a correlation of sectors and firms and individuals homes to have all be shocked at the same time, then I think that will add, you know, how we adjust an account for the long run risk is one question, but also to what extent will tail events lead to kind of additional stresses? I think these are all very active areas of research. And then third, of course, thinking about, I think we've all been kind of bringing up policy interactions, right? So a lot of policy is very well intentioned, but thinking about where we may need to make amendments or corrections to policies that may be having unintended consequences to the extent that we can foresee them in advance, of course. And I think that one of the things that really come up in all of the remarks is that, yes, a lot of the risk is not priced in. And so there's a question of when and how the risk will be priced in. And what does that mean for the macro economy? And the other day I went to a wonderful conversation with some colleagues on the Nature Climate Change paper. And we were talking about, you know, the transition in the energy space. People talk about energy transition, but actually in this space, there's a transition as well in terms of, you know, how the risk gets priced in. And the transition dynamics is really important for thinking about, you know, people's household welfare in this process. If the risk suddenly gets priced in, then we see, you know, a lot of the communities that is highlighted in red in that map, you know, they are going to be very active to go through and how do we prevent things like that happening? I think it's also important. Thank you. And you all also highlighted the equity components of that transition risk and really paying attention to that. So in the queue, we have Lars. Yes. Thank you. Very interesting session. I have because I have two questions. The first one is almost for Laura. I like very much the research that you're doing that's kind of that's looking at the heterogeneous of belief over duration under which these long one risks might be realized. I think that's a very interesting topic and you show some, you know, how that can change perspectives of pricing and financial markets and alike. On that, I had two type of robustness questions. The first is what's the market structure in the background in terms of other ways to hedge the climate risk? And how would that affect the pricing of these bid card contracts? And the second one, I think, is given your models probably largely meant to be qualitative may not be so important, but when I think about these long term risk, I really think that I'd like to think about on broader terms, but long term uncertainty. And so then this issue of how much confidence people have in those beliefs shows up and that confidence itself could spill over to questions about valuation, but the other one is for Penny, when I talk about over valuation risk, I'm kind of curious how you assess that in terms of people when they purchase these homes are speculating about government interventions in the future, government bailout subsidies and the like. And that's going to be fact and simply that could have a big, big impact on the valuation and some of these vulnerable locations. Yeah, no, these are great questions. So at least in our on our debt model, we have we do include insurance as a as an area. But again, I think there's an important question about the incompleteness of insurance and also substitutions across these types of channels to mitigate the risks. Right. So if if somebody perceives that they have default as a channel, then, you know, that may may make insurance less of interest to them. So in we know a stylized fact for flood insurance, United States, take up is very low, despite having premiums that have historically on average been below actually fair prices. But understanding through the lens of belief heterogeneity can at least provide one area to reconcile this where, you know, if people if people are attentive to the risk, but relying on other ways to shoulder these risks or hedge them, then then insurance may look less appealing to them, especially if prices are rising. And then, of course, if people are overly optimistic, insurance may also not look that appealing because the price will be high relative to the expected losses that they have. So I agree. I think there's a lot more work to be done to look at kind of the portfolio of ways, location, decision in situ adaptation and mitigation efforts, both private and public insurance, you know, default in how all of these kind of work in tandem or in substitution, as you're mentioning also substitutes, the substitution for expectations of post disaster aid. In reality, household level eight is is fairly low. But I think but, you know, people may overestimate this. And I think there's really an important role for survey work here, because there's a lot that we can get, you know, in Daryl's great work with kind of experiments and trying to unpack these beliefs and also the correlation of beliefs at the individual level between how we perceive, you know, generosity of insurance versus post disaster aid, etc., to see how people are kind of making these decisions and substituting across these options in their own mind. And then in terms of kind of long term risk, absolutely, I think uncertainty is a big piece of this. We try not to make a big statement as to what the correct belief is, but rather it's a well known finding that there is significant heterogeneity in belief surrounding climate change. So, you know, to the extent that some people may be overestimating future risk, maybe overly pessimistic, that's entirely possible too, as well. But I think, you know, this really begets, again, more study looking at climate beliefs, but also the learning process, spillovers in learning how new information may or may not beget learning because more and more we're seeing this heterogeneity can actually be an important lover for how climate risk is propagated throughout the financial system. Yeah, I think it's important to include the term confidence here. It's not just about beliefs, it's how confident they are in their beliefs. Yes, great point. And then in terms of what people expect of government policy, you're right, that, you know, when we quantify the overvaluation, we're really comparing sort of whether the expected damage is priced into the property values. And part of the reason they are not is because of, you know, the lack of information for households, which is also illustrated by various experiments. And that part of it could be, you know, rational expectation that the government is going to step in and provide some aid, although there are also research that shows that people in general are optimistic about how much aid they're actually going to get from the government. And for me, this sort of highlights an additional thing, which is the policy uncertainties when it comes to, you know, future disaster aid conditions or the provision of insurance at affordable rates, those kind of uncertainty can also be part of the risk going forward. The NFIP has been on short term reauthorization and they haven't been able to get like a long term reauthorization for it. These kind of uncertainties can become really big. And then, you know, in terms of risk rating 2.0, which is which is a new pricing scheme that that is her team I'm currently being filled with all these uncertainties and add up. Thank you very much. Yeah. Yeah, thanks. Thanks for the great talks. Apologies, I had to join kind of in the middle. So I missed Laura, your first talk. So my question we focused a little bit on what I heard later on, but it actually ties in a bit to these comments on heterogeneity and beliefs and incumbents. But we you talked about, Darryl, you talked about, obviously, your presentation was on the effect that providing flood risk information to housing market participants and homebuyers. What effect that can have on on demand. And I'm curious if any of the presenters have thoughts on other avenues through which existing climate risk information can have a big impact on this potential overvaluation or mispricing of particular assets? Obviously, improving our understanding of risk is always a good thing. But given our current views and levels of understanding, I think housing market participants is a very clear area where increased access to that information can result in more efficient markets. But I'm curious if you have thoughts on other other avenues where we can kind of see a particular opportunity for a large impact, simply by increasing access to risk information. That's for anybody, I guess, sorry. Yeah, I can take a first stop at this. So there is a whole question about how people cognitively process information about risk and sometimes, you know, large impacts, small probability events, it's not that easy to understand for them. And so there's research looking at, you know, how you can convey that information. The other thing I think that might be more straightforward for people to understand is in terms of economic cost, you know, the cost of insurance and what is insurance, like how is insurance projected to increase over time information about the future? Those kinds of things is also important, although in the case of insurance in particular, there is a central dilemma, which is that if you increase the cost of insurance, people start dropping them. And, you know, in general, we do want people to have insurance because it's really important source of financial resources for them to rebuild after disaster. Yeah, I guess I don't have a really good idea about this, but then I think that, you know, economic cost is definitely one of the easier to understand things for people. Yeah, so I there's a budding industry of climate projectors that sell like as detailed as possible climate data down to, you know, the the lat long or the G.O.I.D. And their customers tend to be owners of big commercial real estate portfolios. So at least at the moment, those are the people who seem to care the most about this climate data, like I say, believe that there's someone that wouldn't they they're doing what this conference is about. They're trying to macro forecast what their portfolios are going to look like down the line. So that's in a place where they're already looking at information. And then but another place that I think would be really important to get the information in front of people is is for municipalities, state governments, people who are making decisions of also about investments in real estate, where to build a school, you know, whether where to build housing, whether to up zone. I guess this kind of goes back to housing, but there are other there are other things to consider transportation. Just those kinds of urban planning investments. I think getting that in front of their eyes is a good way to have a large effect on the outcomes. And I'll just add I, in addition to kind of information, so, you know, through science, scientists, through public policy and whatnot, information. Disaster events themselves are a big learning tool as well. So I think that can be another useful area for inquiry to see how decisions may change following a disaster when these climate risks may be a lot more salient. There's certainly a temporal element, so people also forget over time. But I have a working paper looking in Vietnam at how households will actually change their allocations, change progressionary savings and also the portfolio, what they're investing in following cycle events. So I think there are a lot of ways that that this can interact with the economy that would then have implications for the broader macroeconomy, but yeah, so I but certainly important area to be thinking about. Thank you very much. We have someone on an iPhone. There's no name attached to it. It's a 603 number. Could could you identify yourself? Well, why don't we go to the next person? Elizabeth, Elizabeth Kaiser. Terrific. Thanks so much. So hi, Beth Kaiser. I'm from the Federal Reserve Board. My question is focused on the perspective of the municipal fiscal authorities themselves. And so my question is really for any and all of the presenters. It seems that there's a real tension here in flood risk, climate risk generically in the context of building locations, insurance markets, individual homeowner decisions between kind of the public policy need for what I understand to be called managed retreat where municipalities, fiscal authorities will actually buy people out of their properties versus the municipalities desire for very big real estate tax revenues, including revenues from new construction in very attractive areas that may have high flood risk or other risks that may not be priced in. How do you think this may play out over time? In terms of both fiscal health in the long run, municipal health for fiscal health for municipalities as well as allocated efficiency. Thanks. I can speak to this. I was a couple of years ago, I talked to the New Jersey League of Municipalities about our flood data and it was interesting to listen to their conversation because they all had different incentives. Like there was a suburban community that was really worried about like property values and there was a more urban community that was worried about people being displaced and where they were going to put them. And there's a larger coordination problem between these communities because if the suburban community does an up zone, it makes it harder for the more urban community to find places for their residents to relocate to if like a large stock of their housing is uninhabitable for a period of time. And then there's also the coordination game between the municipalities and the state and then also with the federal government in terms of how much they might expect to get and how to plan accordingly. So, yeah, a lot of political economy, prisoner, dilemma type problems that may ultimately be needed need to be solved at the federal level, like some kind of, I don't know, incentives or prescriptions for how municipalities have to address these kinds of problems. And I would add so I have a recent study that looks at Comfort Barrier Resources Act, which is a law passed in the 80s that definitely certain and developed areas along the coast and take away financial supervision and federal subsidies for development and disaster aid. And in that study, we find that actually so that policy is extremely effective in curbing development in those like very risky areas, but then they create bill for benefits for nearby areas that encourage development in nearby areas and they also provide flood benefits by conserving from the natural lands along the coast. And so on that we find that the revenue indications for local, local county governments that host these lands are not necessarily negative. And so one of the big takeaways that we get from that research is that, you know, proactive land use choice by local governments that reduce the overall risk in the community and improve resilience might not necessarily be a good thing for them when it comes to adaptation. Thank you very much. And we have Bob Cobb. So I'm going to ask you a lightning round question to round this up. One of the themes I've heard emerging from a lot of the discussions over the last day and a half is that for the United States, a lot of what we were talking about is relatively small at an aggregate national scale. But the distributional effects are not. You know, we saw that for transition in the previous session, we saw that broadly yesterday, lightning round thoughts. What what do you think about how what you're talking about, which is certainly locally significant in coastal counties, for example, could propagate up to something of national macroeconomic significance? Or is there not a channel for that? Yeah, one channel might be through migration. We've already seen people leave the coastal areas for riskier places and home prices have gone up in places like Phoenix and Austin, Florida, which all have high risk. So even if it's one small area, people decide they don't want to live there anymore because of the climate risks or because of the way the government is addressing those risks and they are priced out or they are risked out, that would have spillover effects into surrounding communities and even across the country. I'm thinking large scale withdrawal by insurers could lead to systematic devaluation of properties in the highest risk areas. Yeah, I also think it's it's still an open question about, you know, seeing these as small risks. I think that's an important area for future work. They may actually not be small. So the first paper I talked about looking just at the cycle and risk in this can have significant. I mean, it's not like, you know, double digits percentages in GDP growth, but we do find that that one single climate risk can lead to impacts both to GDP and welfare. So but I also agree with Penny and Daryl's responses. All, you know, the mortgage market and property market. I think that's an easy place to start. We have great data there and we know from the last great recession how, you know, unanticipated risks within, you know, these these the segment of the financial market could lead to very large reverberations on a global scale. So again, I just I think this is an area where a lot more research is needed to understand exactly that question. But, you know, thinking of them as kind of small or regional scale may may not be true. So yeah, I think Laura, you have a very good point. And just just to be clear, it's not just homes in our floodplains. We've got a lot of infrastructure. We've seen companies, electric companies, gas companies, others. Lots of infrastructure, much of our nation's economic engines of growth are located in floodplains that are very vulnerable to sea level rise. And now we've got wildfires as well. So I do think we're seeing just the tip of the iceberg and there is more research needed to delve into the scale of the issue. It's obviously buried in a number of budgets, including a federal budget, which is why the GAO has that high risk list that they put out and flood insurance and crop insurance are always very much on that high risk list. So I guess one key takeaway does seem to be from the session that it's important for us all to know our risk, whether we're homeowners, home buyers, managing these budgets, etc. So just know that the risk shouldn't just be flying under the radar. Quantifying it is going to be critical to making better economic decisions. I'm going to turn it over now. Thank you very much to all our panelists for a very, very engaging session. I'm going to turn it over now to the organizers to tell us a little bit about the work period that's coming up. Yeah, great. Thanks, everyone. Just like all the other sessions, we open the Slido again, but we are breaking for the next hour and we'll reconvene at one p.m. when we we will go into breakout breakout rooms. So thank you, everyone. And yeah, definitely encourage you to add your ideas to the Slido.