What's at Stake? Understanding the Role of Home Equity in Flood Insurance Demand

Liao, Yanjun; Mulder, Philip

doi:10.2139/ssrn.3756332

Cited by 9 publications

(9 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our paper contributes to the understanding of how SLR and increased flood risks affect the housing market (BGL; BGY; Murfin and Spiegel 2020;Hino and Burke 2021;Keys and Mulder 2020;Addoum et al 2021;Bakkensen and Barrage 2022). 7 Our paper also contributes to a growing but important set of papers investigating how the interaction between climate risks and existing government policies, including policies on securitization and insurance subsidies, affects the mortgage market (Issler et al 2020;Liao and Mulder 2021;Sastry 2021;Ouazad and Kahn 2022). Complementary to our paper, the evidence in Liao and Mulder (2021) suggests that mortgage default could act as implicit insurance against climate-related disaster risks.…”

Section: Related Literaturementioning

confidence: 62%

“…7 Our paper also contributes to a growing but important set of papers investigating how the interaction between climate risks and existing government policies, including policies on securitization and insurance subsidies, affects the mortgage market (Issler et al 2020;Liao and Mulder 2021;Sastry 2021;Ouazad and Kahn 2022). Complementary to our paper, the evidence in Liao and Mulder (2021) suggests that mortgage default could act as implicit insurance against climate-related disaster risks. In investigating climate risks as a source of long-run risks that could affect the prices of long-term financial assets/liabilities such as stocks and long-term municipal or sovereign bonds, our analysis is related to those in Bansal et al (2021), Painter (2020), Goldsmith-Pinkham et al (2021, and Barnett and Yannelis (2021).…”

Section: Related Literaturementioning

confidence: 62%

“…Recent papers in the literature have argued that mortgage lenders tend to shift climate risks to government-sponsored enterprises (GSE) through the process of securitization and the sale of mortgages below the conforming loan limits to such institutions. This is possible since GSE securitization rules and fees tend to only reflect current official floodplain maps and not necessarily future SLR risks (e.g., Liao and Mulder 2021;Ouazad and Kahn 2022;Panjwani 2022). If this is indeed the case, then we should expect our empirical results to hold more for the conforming loan segment than for the jumbo segment.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Leveraging the Disagreement on Climate Change: Theory and Evidence

Bakkensen¹,

Phan²,

Wong³

2023

View full text Add to dashboard Cite

We theoretically and empirically investigate how climate risks affect collateralized debt markets. First, we develop a debt model where agents have different beliefs over a long-run risk. In contrast with existing two-period competitiveequilibrium models, our infinite-horizon competitive-search model predicts more pessimistic agents are more likely to make leveraged investments on risky collateral assets. They also tend to use longer maturity debt contracts, which are more exposed to the long-run risk. Second, employing large data on real estate and mortgage transactions, combined with high resolution sea-level-rise maps, we find robust evidence for these findings. We also show how monetary and securitization policies affect mortgage climate risk exposure. Our results highlight the importance of heterogeneous beliefs in understanding the effects of climate change on the financial system.

show abstract

Section: Related Literaturementioning

confidence: 62%

Section: Related Literaturementioning

confidence: 62%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Leveraging the Disagreement on Climate Change: Theory and Evidence

Bakkensen¹,

Phan²,

Wong³

2023

View full text Add to dashboard Cite

show abstract

“…The hedonic residuals at properties with no observed sales are interpolated using space-time kriging to generate best linear unbiased estimators based on the covariance of observed sales as a function of the time and distance between properties (Le & Zidek, 2006;Pyrcz & Deutsch, 2014;Waller & Gotway, 2004). By interpolating residuals from properties with observed sales onto properties without observed sales across a set of discrete quarterly timesteps, a timeseries of property value estimations can be generated at each property.…”

Section: Property Value Modelmentioning

confidence: 99%

Systemic Financial Risk Arising From Residential Flood Losses

et al. 2023

View full text Add to dashboard Cite

show abstract

“…For example, after Hurricane Harvey in 2017, the mortgage delinquency rate at flood damaged properties in Houston increased by 205% (CoreLogic, 2018b). After a flood, property owners may be encouraged to "strategically default", or walk away from the damaged property (Liao & Mulder, 2021) as negative equity reduces the incentive to borrow to repair damages (Melzer, 2017). Other factors associated with a flood event, such as loss of employment and income, may also force property owners to default on their mortgage (Jacobsen et al, 2009;Sarmiento & Miller, 2006).…”

Section: Introductionmentioning

confidence: 99%

Systemic Financial Risk Arising from Residential Flood Losses

Thomson

Zeff

Kleiman

et al. 2022

Preprint

View full text Add to dashboard Cite

Flood impacts to residential properties threaten the resilience of communities and the institutions that support them. These events can cause negative impacts to property-level balance sheets through uninsured damage and property value decreases, which in turn can increase the likelihood of mortgage default and property abandonment. To date, there have been limited attempts to quantify the magnitude and distribution of additional financial consequences that could arise from these processes following flood events. In this work, property-scale financial data, including property sales, mortgage originations, and insurance claims, are used within an analytical framework to quantify flood-related uninsured damages and property value decrease in order to estimate the financial risk that property owners, mortgage lenders, and local governments are exposed to via recovery decisions (i.e., default and/or abandonment). This framework is applied to residential properties in eastern North Carolina following Hurricane Florence (2018). Within the study area, Hurricane Florence generated $366M in observed insured losses and we estimate an additional $1.77B in balance sheet losses (i.e., uninsured damage and property value decrease). In addition, property owners, mortgage lenders, and local governments were exposed to an estimated $562M of risk from the increased likelihood of mortgage default and property abandonment. Areas with lower pre-event property values and lower rates of insurance purchase experienced significantly higher risk of mortgage default and abandonment. The method described provides more highly resolved estimates of how floods can drive systemic financial risk, information that can be useful in developing improved flood resilience strategies.

show abstract

What's at Stake? Understanding the Role of Home Equity in Flood Insurance Demand

Cited by 9 publications

References 25 publications

Leveraging the Disagreement on Climate Change: Theory and Evidence

Leveraging the Disagreement on Climate Change: Theory and Evidence

Systemic Financial Risk Arising From Residential Flood Losses

Systemic Financial Risk Arising from Residential Flood Losses

Contact Info

Product

Resources

About