{"title":"揭示洪水适应方面的差异,促进未来公平的干预措施","authors":"Lidia Cano Pecharroman, ChangHoon Hahn","doi":"arxiv-2312.03843","DOIUrl":null,"url":null,"abstract":"As governments race to implement new climate adaptation policies that prepare\nfor more frequent flooding, they must seek policies that are effective for all\ncommunities and uphold climate justice. This requires evaluating policies not\nonly on their overall effectiveness but also on whether their benefits are felt\nacross all communities. We illustrate the importance of considering such\ndisparities for flood adaptation using the FEMA National Flood Insurance\nProgram Community Rating System and its dataset of $\\sim$2.5 million flood\ninsurance claims. We use ${\\rm C{\\scriptsize AUSAL}F{\\scriptsize LOW}}$, a\ncausal inference method based on deep generative models, to estimate the\ntreatment effect of flood adaptation interventions based on a community's\nincome, diversity, population, flood risk, educational attainment, and\nprecipitation. We find that the program saves communities \\$5,000--15,000 per\nhousehold. However, these savings are not evenly spread across communities. For\nexample, for low-income communities savings sharply decline as flood-risk\nincreases in contrast to their high-income counterparts with all else equal.\nEven among low-income communities, there is a gap in savings between\npredominantly white and non-white communities: savings of predominantly white\ncommunities can be higher by more than \\$6000 per household. As communities\nworldwide ramp up efforts to reduce losses inflicted by floods, simply\nprescribing a series flood adaptation measures is not enough. Programs must\nprovide communities with the necessary technical and economic support to\ncompensate for historical patterns of disenfranchisement, racism, and\ninequality. Future flood adaptation efforts should go beyond reducing losses\noverall and aim to close existing gaps to equitably support communities in the\nrace for climate adaptation.","PeriodicalId":501487,"journal":{"name":"arXiv - QuantFin - Economics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exposing Disparities in Flood Adaptation for Equitable Future Interventions\",\"authors\":\"Lidia Cano Pecharroman, ChangHoon Hahn\",\"doi\":\"arxiv-2312.03843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As governments race to implement new climate adaptation policies that prepare\\nfor more frequent flooding, they must seek policies that are effective for all\\ncommunities and uphold climate justice. This requires evaluating policies not\\nonly on their overall effectiveness but also on whether their benefits are felt\\nacross all communities. We illustrate the importance of considering such\\ndisparities for flood adaptation using the FEMA National Flood Insurance\\nProgram Community Rating System and its dataset of $\\\\sim$2.5 million flood\\ninsurance claims. We use ${\\\\rm C{\\\\scriptsize AUSAL}F{\\\\scriptsize LOW}}$, a\\ncausal inference method based on deep generative models, to estimate the\\ntreatment effect of flood adaptation interventions based on a community's\\nincome, diversity, population, flood risk, educational attainment, and\\nprecipitation. We find that the program saves communities \\\\$5,000--15,000 per\\nhousehold. However, these savings are not evenly spread across communities. For\\nexample, for low-income communities savings sharply decline as flood-risk\\nincreases in contrast to their high-income counterparts with all else equal.\\nEven among low-income communities, there is a gap in savings between\\npredominantly white and non-white communities: savings of predominantly white\\ncommunities can be higher by more than \\\\$6000 per household. As communities\\nworldwide ramp up efforts to reduce losses inflicted by floods, simply\\nprescribing a series flood adaptation measures is not enough. Programs must\\nprovide communities with the necessary technical and economic support to\\ncompensate for historical patterns of disenfranchisement, racism, and\\ninequality. Future flood adaptation efforts should go beyond reducing losses\\noverall and aim to close existing gaps to equitably support communities in the\\nrace for climate adaptation.\",\"PeriodicalId\":501487,\"journal\":{\"name\":\"arXiv - QuantFin - Economics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - QuantFin - Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2312.03843\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2312.03843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exposing Disparities in Flood Adaptation for Equitable Future Interventions
As governments race to implement new climate adaptation policies that prepare
for more frequent flooding, they must seek policies that are effective for all
communities and uphold climate justice. This requires evaluating policies not
only on their overall effectiveness but also on whether their benefits are felt
across all communities. We illustrate the importance of considering such
disparities for flood adaptation using the FEMA National Flood Insurance
Program Community Rating System and its dataset of $\sim$2.5 million flood
insurance claims. We use ${\rm C{\scriptsize AUSAL}F{\scriptsize LOW}}$, a
causal inference method based on deep generative models, to estimate the
treatment effect of flood adaptation interventions based on a community's
income, diversity, population, flood risk, educational attainment, and
precipitation. We find that the program saves communities \$5,000--15,000 per
household. However, these savings are not evenly spread across communities. For
example, for low-income communities savings sharply decline as flood-risk
increases in contrast to their high-income counterparts with all else equal.
Even among low-income communities, there is a gap in savings between
predominantly white and non-white communities: savings of predominantly white
communities can be higher by more than \$6000 per household. As communities
worldwide ramp up efforts to reduce losses inflicted by floods, simply
prescribing a series flood adaptation measures is not enough. Programs must
provide communities with the necessary technical and economic support to
compensate for historical patterns of disenfranchisement, racism, and
inequality. Future flood adaptation efforts should go beyond reducing losses
overall and aim to close existing gaps to equitably support communities in the
race for climate adaptation.