TY - JOUR
T1 - Impacts of extreme weather events on mortgage risks and their evolution under climate change
T2 - A case study on Florida
AU - Calabrese, Raffaella
AU - Dombrowski, Timothy
AU - Mandel, Antoine
AU - Pace, R. Kelley
AU - Zanin, Luca
N1 - Funding Information:
We would like to thank the Editor and the reviewers for their constructive suggestions which helped to improve the paper. The paper was presented at several seminars and conferences, including the 20th International Conference on Credit Risk Evaluation – Compound Risk: Climate, Disaster, Finance, Pandemic, the 38th Annual Meeting and Conference of the American Real Estate Society, the DXDE 2021: Digital Transformation and Digital Economics, the U.S. Federal Housing Finance Agency seminar, and the 11th Annual Research Workshop - Technological Innovation, Climate Finance and Banking Regulation organized by European Banking Authority. We thank the participants at these events for their helpful comments and suggestions. Antoine Mandel acknowledges funding from the European Union's Horizon Europe research and innovation program under grant agreement DECIPHER nb 101056898. Raffaella Calabrese acknowledges the support of the ESRC code ES/W0110259/1.
Funding Information:
We would like to thank the Editor and the reviewers for their constructive suggestions which helped to improve the paper. The paper was presented at several seminars and conferences, including the 20th International Conference on Credit Risk Evaluation – Compound Risk: Climate, Disaster, Finance, Pandemic, the 38th Annual Meeting and Conference of the American Real Estate Society, the DXDE 2021: Digital Transformation and Digital Economics, the U.S. Federal Housing Finance Agency seminar, and the 11th Annual Research Workshop - Technological Innovation, Climate Finance and Banking Regulation organized by European Banking Authority. We thank the participants at these events for their helpful comments and suggestions. Antoine Mandel acknowledges funding from the European Union’s Horizon Europe research and innovation program under grant agreement DECIPHER nb 101056898 . Raffaella Calabrese acknowledges the support of the ESRC code ES/W0110259/1 .
Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2024/4/1
Y1 - 2024/4/1
N2 - We develop an additive Cox proportional hazard model with time-varying covariates, including spatio-temporal characteristics of weather events, to study the impact of weather extremes (heavy rains and tropical cyclones) on the probability of mortgage default and prepayment. We compare the survival model with a flexible logistic model and an extreme gradient boosting algorithm. We estimate the models on a portfolio of mortgages in Florida, consisting of 69,046 loans and 3,707,831 loan-month observations with localization data at the five-digit ZIP code level. We find a statistically significant and non-linear impact of tropical cyclone intensity on default as well as a significant impact of heavy rains in areas with large exposure to flood risks. These findings confirm existing results in the literature and also provide estimates of the impact of the extreme event characteristics on mortgage risk, e.g. the impact of tropical cyclones on default more than doubles in magnitude when moving from a hurricane of category two to a hurricane of category three or more. We build on the identified effect of exposure to flood risk (in interaction with heavy rainfall) on mortgage default to perform a scenario analysis of the future impacts of climate change using the First Street flood model, which provides projections of exposure to floods in 2050 under RCP 4.5. We find a systematic increase in risk under climate change that can vary based on the scenario of extreme events considered. Climate-adjusted credit risk allows risk managers to better evaluate the impact of climate-related risks on mortgage portfolios.
AB - We develop an additive Cox proportional hazard model with time-varying covariates, including spatio-temporal characteristics of weather events, to study the impact of weather extremes (heavy rains and tropical cyclones) on the probability of mortgage default and prepayment. We compare the survival model with a flexible logistic model and an extreme gradient boosting algorithm. We estimate the models on a portfolio of mortgages in Florida, consisting of 69,046 loans and 3,707,831 loan-month observations with localization data at the five-digit ZIP code level. We find a statistically significant and non-linear impact of tropical cyclone intensity on default as well as a significant impact of heavy rains in areas with large exposure to flood risks. These findings confirm existing results in the literature and also provide estimates of the impact of the extreme event characteristics on mortgage risk, e.g. the impact of tropical cyclones on default more than doubles in magnitude when moving from a hurricane of category two to a hurricane of category three or more. We build on the identified effect of exposure to flood risk (in interaction with heavy rainfall) on mortgage default to perform a scenario analysis of the future impacts of climate change using the First Street flood model, which provides projections of exposure to floods in 2050 under RCP 4.5. We find a systematic increase in risk under climate change that can vary based on the scenario of extreme events considered. Climate-adjusted credit risk allows risk managers to better evaluate the impact of climate-related risks on mortgage portfolios.
KW - OR in banking
KW - credit risk
KW - climate change
KW - mortgage
KW - survival analysis
U2 - 10.1016/j.ejor.2023.11.022
DO - 10.1016/j.ejor.2023.11.022
M3 - Article
SN - 0377-2217
VL - 314
SP - 377
EP - 392
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 1
ER -