Full Citation

Title: Enhancing Post-Disaster Recovery Modeling Through High-Fidelity Household Income Estimation

Citation Type: Conference Paper

Publication Year: 2022

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Abstract: Recent disasters have shown that income plays a central role in determining the capacity of impacted households to cope with the shock and recover from it. Researchers often rely on random sampling to generate synthetic household income from aggregated Census data. This conventional approach imposes limitations towards proposing realistic policies. A method is introduced to deduce minimum household income for single-family homeowners using publicly available data via the tax assessor and current population survey. Post-earthquake housing recovery simulations are used to evaluate the advantages of the proposed income estimation method relative to the germane random sampling approach. Preliminary results with the proposed method show a reduction in the number of low-income households assigned to high-valued dwellings. Results also suggest that the random sampling approach leads to inflated recovery delays and overestimates the vulnerability of select low-income households.

Url: https://www.jackwbaker.com/Publications/Zhang_et_al_(2022)_HHincome,_NCEE.pdf

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Authors: Zhang, Jimmy; Costa, Rodrigo; Zsarnóczay, Ádam; Baker, Jack Wesley

Conference Name: Proceedings of the 12th National Conference in Earthquake Engineering

Publisher Location: Salt Lake City

Data Collections: IPUMS USA

Topics: Natural Resource Management, Poverty and Welfare

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