Characterizing relationship between demand surge and post-disaster reconstruction capacity considering poverty rates

贫穷 工资 经济 浪涌 计量经济学 人口经济学 地理 经济增长 劳动经济学 气象学
作者
Sooin Kim,Mohsen Shahandashti
出处
期刊:International journal of disaster risk reduction [Elsevier BV]
卷期号:76: 103014-103014 被引量:8
标识
DOI:10.1016/j.ijdrr.2022.103014
摘要

The post-disaster reconstruction capacity of communities determines their survival after large-scale disasters. Unexpected and substantial increases in construction costs in response to the significant reconstruction demands following disasters, known as demand surge, can decrease reconstruction speed and limit the reconstruction capacity of communities. The objective of this research is to investigate the relationships between labor wage fluctuation (representing demand surge) and change in building permits (representing reconstruction capacity) of various communities considering their poverty rates. The county-level data of building permits, construction labor wages, and poverty rates were collected for the affected counties by devastating hurricanes. Multiple regression models were utilized to quantify the relationships between wage fluctuation and change in building permits in counties with above-average and below-average state poverty rates. The results show that wage fluctuation is negatively correlated with the change in building permits in counties with above-average poverty rates. In contrast, fluctuation does not show a statistically significant correlation with the change in building permits in counties with below-average poverty rates. These findings indicate that demand surge has a statistically significant negative relationship with the reconstruction capacity of counties with above-average poverty rates, while there is no meaningful relationship with the reconstruction capacity of counties with below-average poverty rates. The findings of this research can assist risk-mitigation agencies in identifying more sensitive communities, prioritizing the reconstruction needs, and enhancing risk reduction strategies considering the socioeconomic characteristics of communities.
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