In this week’s episode, host Kristin Hayes talks with Penny Liao, a scholar of behavioral and market responses to environmental risk, who joined Resources for the Future as a fellow earlier this month. Liao elaborates on a new working paper she coauthored about how home equity shapes a household’s decision to purchase flood insurance. In the end, Liao finds that homeowners with more home equity are especially likely to purchase flood insurance because they do not want to default on their mortgage, while households with highly leveraged mortgages have less incentive to insure against flood risks.
Listen to the Podcast
- Flood risks are escalating: “Flooding is a very expensive type of disaster, both in aggregate and for individual homeowners. In aggregate, it cost about $15 billion annually over the past decade. For individuals, when their home is flooded, the damage can easily be tens of thousands of dollars. For example, in 2019, the average flood insurance claim was $52,000. In 2017, when there were particularly severe hurricanes, the average claim went to more than $90,000.” (10:26)
- Displaced risk for homeowners who don’t purchase flood insurance: “Homeowners with a highly leveraged mortgage do not fully internalize their flood risk. Instead, part of the risk is transferred to the lenders, but ultimately, a lot of these loans are securitized by government-sponsored enterprises, such as Fannie Mae and Freddie Mac. Taxpayer dollars are on the line, and this is an implicit cross-subsidy to homeowners exposed to flood risk.” (23:01)
- Potential reforms for flood insurance programs: “It’s worth considering expanding the flood insurance mandate to beyond the 100-year floodplains, because that risk cutoff is pretty artificial. Homes outside that zone are also exposed to quite substantial levels of risk … It’s also important for flood insurers to price in these risk-reduction measures and encourage people to undertake them. These are things like receiving a discount when you have undertaken certain floodproofing measures.” (24:20)
Top of the Stack
- “What's at Stake? Understanding the Role of Home Equity in Flood Insurance Demand” by Penny Liao and Philip Mulder
- “The Tragedy of the Commons” by Garrett Hardin
- “The Problem of Social Cost” by Ronald Coase
- Bewilderment by Richard Powers
- The Overstory by Richard Powers
The Full Transcript
Kristin Hayes: Hello, and welcome to Resources Radio, a weekly podcast for Resources for the Future. I'm your host, Kristin Hayes. My guest today is Penny Liao, who started as an RFF Fellow as of August 1st, 2021, so the weekend in which we are recording.
Penny most recently finished up a postdoctoral fellowship at the Wharton Risk Center at the University of Pennsylvania, and before that, she received her PhD in economics at the University of California, San Diego (UCSD) in 2019. Penny's primary research interests are in behavioral and market responses to extreme weather events and environmental risks and how policies can be designed to facilitate efficient adaptation.
My conversation with Penny is the first in a pair of episodes designed to introduce our listening audience to RFF's newest wonderful researchers. It's a bit of a departure from our previous episode content. I recognize that we typically focus on a topic far more than on an individual, but today, in the spirit of welcoming Penny to the RFF family, I'd like to add in a few extra "get to know you" questions, before we discuss Penny's research on flood insurance and home equity. Call it the host's prerogative. Stay with us.
Penny, welcome to Resources Radio, and welcome to Resources for the Future. It's very nice to have you.
Penny Liao: Thank you.
Kristin Hayes: This month marks the beginning of your official tenure at RFF, and we're really pleased to have you in the family. Can you tell our listeners just a little bit about the path that brought you to this point?
Penny Liao: Yeah. Thank you for having me Kristin. I'm very happy to be part of RFF and to be talking to you today.
I actually started on this path to be an environmental economist by chance. I was an undergraduate in economics at the University of Hong Kong, and nobody in my university studies environmental economics. The field does not exist there. But I happened to know an environmental economist teaching at another university in Hong Kong, named Professor Bill Barron, and he was incredibly passionate about the field. As soon as he learned that I'm an undergrad in econ, he immediately recommended two papers for me to read.
Those are “The Tragedy of the Commons,” by Garrett Hardin, and “The Problem of Social Cost,” by Ronald Coase, and these papers blew my mind. They're such seminal papers in the field, and they laid out very profound and powerful ideas in a very accessible way that I, as a second year undergrad, could understand. I remember being so fascinated by the idea that you can apply an economic lens to environmental problems. That appeals to me a lot, because growing up in China, I've seen the tension between economic development and environmental quality. And environmental economics seems to have this potential for confronting this tension and finding a path forward.
So this fascination has stuck with me ever since. I started working for an environmental and urban policy think tank in Hong Kong, called Civic Exchange. Then I went to UCSD to pursue a PhD in economics, specializing in environmental economics. When I completed my PhD, I was already working on climate and disaster impacts.
I then joined the Wharton Risk Center as a postdoctoral researcher. The Risk Center deals a lot with questions of risk, how people make decisions related to risks, and how risks get diversified and things like that. That's when I started thinking about disaster risk management and adaptation more systematically.
Kristin Hayes: So interesting. I love the beginning of that anecdote, just for the fact that it reminds me how much of a difference an individual professor, or just an individual passionate person of any variety, can really make a difference in someone's trajectory.
But that's great. It sounds like you really kind of blazed your own path a little bit, in terms of following your passions and bringing things together in a way that wasn't super common.
Penny Liao: I was definitely very lucky to have such good mentors along the way. I think that during your formative years, running into these people really helps.
Kristin Hayes: Well, that's great. That's wonderful and more than I knew, so I'm very pleased to know that myself. So let's talk about adaptation for just a second.
I would suggest that research on adaptation measures seems to be of increasing importance, given the visibility of extreme weather events, and unfortunately, due to our relative inaction on mitigation, as well. You said a little bit about this, but can you say a little bit more about why you chose to focus on disasters, risks, and adaptation? Why did that really capture your imagination?
Penny Liao: First of all, even without climate change, disaster risk is a very important and interesting topic to me. There are catastrophic events throughout human history that have destroyed the lives and livelihoods of so many people. We now have more advanced physical knowledge and modeling techniques than before, and we know that we can see this as a risk management problem.
From a public policy point of view, I think it's an important question: how do we build a robust system, to reflect and diversify the risks, and to protect vulnerable populations from the realizations of those risks? Then on top of that, we have climate change, which makes things much worse.
I think you spell it out really well in your question. The relative inaction in mitigation makes adaptation more important. That's also the realization I've come to during graduate school, and I think that there's a lot of room for improvement when it comes to adaptation.
This summer, we're seeing a record number of extreme weather events and disasters across the world. And it seems clear that the infrastructure in many places is not really well defined to handle such events. There are a lot of opportunities right now for governments to take note and be more prepared for unexpected events like this. It's not just the governments—individuals, businesses, and other entities can also take actions to be prepared. There are a lot of open questions about whether we have the right incentive structure in place, for these agents to take the necessary adaptation measures.
Kristin Hayes: That makes a lot of sense. At RFF we focus on policy, and the policy levers are incredibly important, but you're right to point out that adaptation is going to happen across a wide range of jurisdictions, including everything from the homeowner to the insurance company, to the local government, state government, all the way up to the federal government. So the range of questions and the range of players is very wide. It makes sense that there'd be just a lot that we still need to figure out.
Penny Liao: Yeah, certainly. I mean, even for individuals and businesses, what the current policy is also affects their choices. That's really important.
Kristin Hayes: Let me ask you one more introductory question, though I do want to spend the bulk of our time talking about some of your recent research. You mentioned early on that you attended university and got your undergraduate education in Hong Kong, before coming to the United States, and that you grew up in China.
Can I just ask for a global perspective in how you see the conversation around mitigation, and perhaps adaptation, in particular, being different in a place like Hong Kong compared to the United States? Are there different policy levers available? How does the conversation look?
Penny Liao: Right, so there are certainly both differences and similarities. First of all, in Hong Kong, climate change is not a politically charged issue, so I think the general public might not consider it a huge concern, compared to the economy, for example. But they do overwhelmingly support mitigating carbon emissions within Hong Kong. In terms of adaptation, Hong Kong is a predominantly urban environment: most people live in an urban environment, and they have exposure to extreme heat and tropical cycles. The infrastructure there has more or less been adapted to such events, and there are management practices trying to adapt to these risks.
But going forward, it's unclear whether the existing infrastructure is going to hold up in more extreme scenarios of heat, and things like storm surges coming from sea level rise. I think that is actually universal to a lot of other places, as well, which are all facing that uncertainty.
There is also a pretty high level of inequality. I'm not sure I have seen enough discussion there about what this means, in terms of exposure to climate impacts by different groups. I think that the equity concern is true, both in Hong Kong and in the United States. I think that there are definitely differences, but also a lot of similarities.
Kristin Hayes: Interesting. Thank you for that context, in that trans-Pacific perspective there.
You're wrapping up some work on flood insurance and home equity, and you and your authors look at, and I'm going to quote here for a second, how "mortgage default may be a form of implicit insurance against disaster risk for leveraged households." Can you explain that hypothesis a little bit more, just kind of ground us in what you're looking at?
Penny Liao: Yes, definitely. This paper is with Philip Mulder, who's a graduate student at Wharton. In the paper, we're interested in looking at flood insurance, but let me first give you some context.
Flooding is a very expensive type of disaster, both in aggregate and for individual homeowners. In aggregate, it cost about $15 billion annually, over the past decade. For individuals, when their home is flooded, the damage can easily be tens of thousands of dollars. For example, in 2019, the average flood insurance claim was $52,000. In 2017, when there were particularly severe hurricanes, the average claim went to more than $90,000.
Kristin Hayes: Wow. And is that just in the United States?
Penny Liao: That's just in the United States, yes. These are flood insurance claims in the United States. They're very high numbers for a normal household if they don't have insurance. In the past, we’ve seen that flooding leads to higher rates of mortgage default and foreclosures.
What that means is that some homeowners, instead of paying to repair the house out of pocket, would rather default from their mortgage and give up their home equity. Now, this can be a rational choice when the homeowner has a low level of home equity but high flood damage. So in this case, we can think of mortgage default as a kind of high deductible insurance policy. The deductible is the home equity, but that's all the homeowner's going to lose when the flood damage goes beyond that.
Kristin Hayes: So what you're looking at is that ratio between levels of home equity, and how much people are willing to default on that in the case of significant damage. Is that right?
Penny Liao: Exactly, yes. When you mention that the level of equity matters, that's exactly the key here. If you have a lot of home equity, then you wouldn't want to default, in any case, so you cannot rely on this implicit insurance. In that case, you would be better off buying formal flood insurance. So the main prediction here is that the more home equity you have, the more you're willing to pay for flood insurance.
Kristin Hayes: Interesting. I hope we can talk about this a little bit further, but it sounds like there may be some questions around inequality baked into this research as well. Hopefully we can talk about that, but first another grounding question. You took advantage of some previous fluctuations in housing market prices, to kind of tease out this relationship between home equity and insurance uptake. Can you explain just a little bit more about that, about the data sources that you used, how you found a moment in time when you felt like you'd be able to look at this question robustly?
Penny Liao: As I've mentioned, the main relationship we want to test for is that higher home equity increases flood insurance demand. For flood insurance data, the main source we used comes from the National Flood Insurance Program (NFIP).
This is a public program operated by the Federal Emergency Management Agency (FEMA), and it provides around 95 percent of all flood insurance in the United States. We're capturing the vast majority of the market, because historically, private insurance companies are not willing to provide flood insurance coverage.
FEMA has published policy-level data in its open FEMA website. So, it's a great data source for researchers who are interested in studying flood insurance, and that's the data we used. We collected a number of other data to supplement it as controls, and to do additional exercises, but I’m not going into detail here.
The most tricky thing in this research is actually a challenge in the research design, because home equity is correlated with other important factors in flood insurance demand, such as income, education, or risk attitudes. If we directly look at the relationship between home equity and flood insurance demand, it's going to capture some of these correlations, so we're not going to be able to identify the causal relationship.
In order to do that, we needed to find something that drives home equity, but not these other things. So for that, we used sudden changes in housing prices during the housing boom and bust in the early 2000s. Around this time, we observed that there was a sudden price acceleration in some housing markets, but not others. In these housing markets, the price first grows smoothly. Then, around between 2003 to 2005, there was a sudden acceleration, where the price of new houses started growing much faster. This variation has been studied in the housing literature, and that's also where our inspiration comes from. The housing literature has shown that this variation is likely to be speculative. And it's independent from fundamental changes in economic and demographic conditions.
This drives large changes in home equity for many homeowners, but it does not change, for example, their underlying flood risk, or the expected cause of flooding for them, because they're still living in the same buildings. This gives us a good opportunity to identify the causal effect of home equity on flood insurance demand, while holding these other factors constant.
Kristin Hayes: Also, as you said, holding things like their baseline levels of education and levels of income, is feasible because it’s over a short enough period that those things are actually just relatively constant, as well? Is that it?
Penny Liao: Yes. It has been shown that, in these markets with a higher housing boom, it's not correlated with, for example, how education levels are evolving. Then the same for income: we have controlled for income in our regressions. So we're holding that constant as well.
Kristin Hayes: One last question about the stage setting here is, were you focused on a particular geographic region? Or were you looking at this across a fairly wide spread of American households?
Penny Liao: Yeah, so we are basically looking at all the metropolitan statistical areas (MSAs) across the entire United States.
Kristin Hayes: Okay. I feel like I always tease our listeners with all of my introductory questions, but let's hear about the findings now. What relationships did you discover? And how do you and your coauthors explain what you found?
Penny Liao: Yeah, definitely. The first thing we see is that flood insurance take-up indeed increases more in high boom markets, when compared to low boom markets. But more importantly, we're able to estimate how flood insurance take-up changes over time, in response to that shock, and trace that out over time.
When we looked at this, we found that the trajectory of insurance take-up correlates really well with the trajectory of housing prices in response to the same housing market shocks. This suggests strongly to us that there is a direct relationship between the two, so we're able to estimate this relationship directly.
We find that a 1 percent increase in housing prices leads to a 0.3 percent increase in flood insurance demand. To put this in context, this is twice the effect of a 1 percent drop in insurance premium. That's a primary factor in insurance demand, so this suggests that there’s quite a substantial relationship.
We also find other patterns that are very telling. For example, NFIP households that live in 100-year floodplains are mandated to buy flood insurance, if they have a federally backed mortgage. But outside of the 100-year floodplains there's no mandate whatsoever, so the decision is completely voluntary. We find that this is largely driven by those households living outside of the 100-year floodplains. So we're capturing this conscious decision: these are voluntary choices people are making.
We're also looking at groups of homes that got built during the housing boom. So these houses were built between 2003 to 2005 and were sold around the same time. Then, when the housing bust started, their prices started dropping, and they still have a pretty large outstanding mortgage. These houses are likely to have pretty low levels of home equity, or even negative home equity. We find that has a particularly large effect, as we see these policies being dropped during the bust. That also strongly points to home equity being the causal factor here.
Now, to further establish that this is really driven by a mortgage default mechanism, we looked at how things were different across the MSAs with different foreclosure costs. Here, by foreclosure cost we mean things like "How soon will I be evicted from the house? Would I be charged a large fee by the lender if I did?" This could vary across states based on their foreclosure laws.
So some states require all the foreclosures to go to court, and these are called judicial requirements. When there's a judicial requirement, it protects the borrower's interest. We find that indeed, in these places, the relationship between home equity and insurance demand is much stronger than the places without the judicial requirement. So that also supports the mechanism.
Then we also test a number of other auxiliary predictions and rule out some alternative mechanisms. I'm happy to go over them, but I'm not sure we have time.
Kristin Hayes: I think we're doing okay on time, if there's another one or two that you want to highlight. It sounds like you guys really mined this information, so feel free to share a few more.
Penny Liao: Yeah, definitely. One important alternative mechanism we looked into is the liquidity mechanism. In this mechanism, home equity can also drive flood insurance demand, in the sense that if you have more home equity, maybe you're better equipped to borrow, and that allows you to better afford to pay the flood insurance premium.
In order to test that, we looked at the insurance renewal rate, and we focused on one-year renewal rates because one year is a short enough time frame that households are not going to think that they learn something about their local flood risk. Insurance renewal rate has been shown in the literature to be strongly driven by liquidity conditions.
So if this is really a liquidity mechanism, we would expect the one-year renewal rate to go up by a lot, because the liquidity condition would be improving. But when we looked into the data, we did not see that at all. That helped rule out the idea that it is actually driven by improving liquidity conditions from higher home equity.
Kristin Hayes: It sounds like you did a tremendous amount of digging around with the information you had, and thank you for sharing those findings. Just to bring it back to the higher level, how do you see what you learned affecting future decisionmaking? In other words, what would you want policymakers and other decisionmakers to take away from what you've done, as they're either designing future flood insurance programs, or thinking about how to better protect homeowners or landscapes in the future?
Penny Liao: Yeah, so that's a very good question. The first implication coming out from the findings is that homeowners with a highly leveraged mortgage do not fully internalize their flood risk. Instead, part of the risk is transferred to the lenders, but ultimately, a lot of these loans are securitized by government-sponsored enterprises (GSEs), such as Fannie Mae and Freddie Mac.
Taxpayer dollars are on the line, and this is an implicit cross-subsidy to homeowners exposed to flood risk. It leads to the second implication, which is that the implicit subsidy here can distort incentives by these homeowners to insure, which we have shown in the paper. It was similarly a factor in people’s incentive to take adaptation measures, such as floodproofing their homes.
We think that some possible solutions to address this problem of incentive is to focus on reflecting the risk in the mortgage system, especially for homes outside of the 100-year floodplains, as we find that's where the effect is. The GSEs, for example, could consider pricing the risk they have taken on, such as charging a higher fee to securitize at-risk loans without insurance coverage.
Alternatively, it's worth considering expanding the flood insurance mandate to beyond the 100-year floodplains, because that risk cutoff—the 1 percent risk cutoff—is pretty artificial. Homes outside that zone are also exposed to quite substantial levels of risk. I've also mentioned the incentive to take adaptation measures. So it's also important for flood insurers to price in these risk-reduction measures as a way to encourage people to undertake them. These are things like receiving a discount when you have undertaken certain floodproofing measures.
Recently, we do see some promising steps taken by different federal agencies which I think are going in the right direction. For example, FEMA has come out with Risk Rating 2.0, which aims to provide more accurate risk-based pricing to the insurers. The Federal Housing Finance Agency, which is the main regulator of the GSEs, issued a request for input on climate and disaster risk in April, which reflects them giving this issue real attention. So I think it will be very interesting to see where these efforts take us; they could even be future research topics.
Kristin Hayes: Sure, yeah. It sounds like it, sure. Penny, thank you so much for explaining all of that so clearly and for grounding us in the work that you're doing.
As you get started in your time at RFF, I'm going to throw in an unexpected question here. What do you hope to work on as you start working at RFF, building on what you've been doing in the past, as well as issues that you've been talking about with colleagues on staff? Are there things that you're particularly excited about tackling in your ongoing research career?
Penny Liao: Yeah, definitely. So I'm going to continue this line of work, in general, thinking more about how we handle risk, especially as climate change is increasing those risks. I am already starting to think of collaborating with RFF colleagues, looking at climate impacts on businesses and how they're able to handle that risk. That is one area that I'm hoping to move into.
Kristin Hayes: Great. Penny, thank you again for joining me on Resources Radio. It's great to have a chance to hear more about your background and your research, and share that with our listening audience.
We have reached the time for our closing feature, Top of the Stack. And I wondered if I could ask you to sort of recommend other good content for our listeners, that either has been on the top of your stack for a while, or something new that's crossed your path?
Penny Liao: Yeah. I was checking out the longlist of this year's Booker Prize. I found out that Richard Powers is coming out with a new book, and it's called Bewilderment.
I read his last book, The Understory, which is about a love of trees and several people’s life journeys to fight against deforestation. I just find his writing so incredibly beautiful, especially when he writes about nature. This new book follows a father, who's an astrobiologist, and his son, who's a troubled kid but also loves animals and nature. It seems like there's a lot of interwoven themes in this book. It's really imaginative. But on the other hand, nature is also a large part of the themes. So I think it might be interesting for the listeners of this podcast to check out.
Kristin Hayes: Great. Well, thank you for that recommendation, and yeah, again, welcome to RFF. It's great to have you with us, and look forward to hearing more in the future.
Penny Liao: Thank you so much for having me. This is fun.
Kristin Hayes: You've been listening to Resources Radio. Learn how to support Resources for the Future at rff.org/support. If you have a minute, we'd really appreciate you leaving us a rating or a comment on your podcast platform of choice. Also feel free to send us your suggestions for future episodes. Resources Radio is a podcast from Resources for the Future. RFF is an independent, nonprofit research institution in Washington, DC. Our mission is to improve environmental energy and natural resource decisions through impartial economic research and policy engagement.
The views expressed on this podcast are solely those of the podcast guests, and may differ from those of RFF experts, its officers or its directors. RFF does not take positions on specific legislative proposals. Resources Radio is produced by Elizabeth Wason, with music by Daniel Raimi. Join us next week for another episode.