Costa, Rodrigo; Wang, Chenbo; Baker, Jack W; (2022) Logistic Models Linking Household Recovery Capacity to Demographic Characteristics. Presented at: 13th International Conference on Structural Safety & Reliability, Shanghai, China.

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Abstract

American Community Survey data are used to build logistic regression models that predict the capacity of owner households to finance the post-earthquake repair of their homes. Having high income and a paid mortgage are used as proxies for the ease of access to financing. We find that households with limited knowledge of English and those with elderly members are the least likely to have a high income. Households with high income and those who have recently moved to their current homes are the most likely to have a mortgage. An example application considering post-earthquake housing recovery in San Francisco is presented. The example demonstrates a strong disparity in the recovery capacity of households based on their demographics. The developed models have important implications for post-earthquake housing recovery as they help to identify the demographics that make households less capable of repairing their homes after an earthquake.

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