Insurers’ Loss Portfolio Similarity and Climate Risk Insurance Cost: A Spatial Analysis of US Homeowners Insurance Market

This study examines the geographical spillover of the state-level average homeowners insurance cost for 48 US contiguous states. We estimate a panel spatial Durbin model with state and year fixed effect for data between 2001 and 2018. We found a significant positive spillover of average homeowners insurance cost as indicated by a large spatial autoregressive coefficient in the baseline model. We also found a positive relationship between underwriters’ loss portfolio similarity and the average homeowners insurance cost. We conduct several robustness tests and show that the baseline results are robust if against potential biases due to heterogenous state-level insurance regulation, an alternatively defined spatial weighting matrix, and the usage of average homeowners cost for the dominant policy form (the HO3 policy). We also adopt the generalized spatial two-step least squares to mitigate the bias due to endogenous explanatory variables and find that the results are consistent with these reported for the baseline model.

Authors

Publication Details

Journal
Risks
Published
2025-02-18
DOI
https://doi.org/10.3390/risks13020036
Primary Topic
Housing Market and Economics
Type
article
Field-Weighted Citation Impact
0.00

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article

Insurers’ Loss Portfolio Similarity and Climate Risk Insurance Cost: A Spatial Analysis of US Homeowners Insurance Market

Tao Sun
Risks
Housing Market and Economics
article

Insurers’ Loss Portfolio Similarity and Climate Risk Insurance Cost: A Spatial Analysis of US Homeowners Insurance Market

Tao Sun
article en

Abstract

This study examines the geographical spillover of the state-level average homeowners insurance cost for 48 US contiguous states. We estimate a panel spatial Durbin model with state and year fixed effect for data between 2001 and 2018. We found a significant positive spillover of average homeowners insurance cost as indicated by a large spatial autoregressive coefficient in the baseline model. We also found a positive relationship between underwriters’ loss portfolio similarity and the average homeowners insurance cost. We conduct several robustness tests and show that the baseline results are robust if against potential biases due to heterogenous state-level insurance regulation, an alternatively defined spatial weighting matrix, and the usage of average homeowners cost for the dominant policy form (the HO3 policy). We also adopt the generalized spatial two-step least squares to mitigate the bias due to endogenous explanatory variables and find that the results are consistent with these reported for the baseline model.

RisksVol. 13(2)
Lingnan University
Openalex Percentile: Top 96%
Housing Market and Economics
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