Housing Reconstruction Demand Surge: Measurement, Modeling, And Vulnerability Assessment

住房重建需求激增：测量、建模和脆弱性评估

• 批准号: 2155201
• 负责人: Mohsen Shahandashti
• 金额: $ 24.99万
• 依托单位: University of Texas at Arlington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2155201&HistoricalAwards=false
• 关键词: Housing; Reconstruction; Demand; Surge; Measurement

Significant post-disaster cost escalations often slow down repair process, magnify inequality, and amplify underinsurance problem. This research will reveal vulnerable characteristics in regional housing construction markets and identify effective disaster-related policies to alleviate these vulnerabilities. It will help identify the construction capacity gaps that cause the construction cost escalation following natural disasters. The discovery is critical for raising awareness, developing a greater construction capacity, setting effective reconstruction goals, initiating risk mitigation and resourcing strategies, and enforcing effective regulations and policies. Cutting the housing recovery time and cost through effective pre-planning could be realized. This project also aims to address the critical shortage of talents capable of leading post-disaster reconstruction in the civil engineering discipline. Hispanics and women graduate and undergraduate students at the Hispanic-serving University of Texas at Arlington (UTA) will participate in every step of this project. This project will enable students to work with city planners to lead stakeholder involvement in disadvantaged communities.This project will address fundamental limitations of existing demand surge models by 1) creating non-hazard econometric baselines for housing construction cost variations, 2) creating an econometric measurement method for quantifying post-disaster construction cost escalations, 3) creating spatiotemporal econometric models to represent the housing reconstruction demand surge, and assessing the housing reconstruction vulnerability of communities, and 4) quantifying the impacts of disaster-related policies on housing reconstruction. This project will generate new knowledge at the nexus of three critical disciplines: Housing Construction, Economics, and Built Environment Resilience. The research will transform existing construction demand surge models by establishing links between pre-disaster construction market conditions and post-disaster construction cost escalations. To that end, spatiotemporal econometric models, such as spatial panel data models, will use data from more than 600 U.S. counties affected by large-scale natural disasters over the past ten years, as well as data from their neighboring counties. These models will consider different circumstances based on a range of non-hazard to extreme hazard conditions. Difference-in-difference panel data models will estimate the effect of disaster-related policies (ranging from local to federal). The research team will engage federal, state, and local governments to identify and evaluate various disaster-related policies.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

灾后成本的显著上升往往会减缓修复进程，放大不平等，并放大保险不足问题。这项研究将揭示区域住房建筑市场的脆弱特征，并确定有效的灾害相关政策来缓解这些脆弱性。它将有助于确定导致自然灾害后建设成本上升的建设能力缺口。这一发现对于提高认识、发展更大的建设能力、制定有效的重建目标、启动风险缓解和资源分配战略以及执行有效的法规和政策至关重要。通过有效的前期规划，可以减少住房恢复的时间和成本。该项目还旨在解决土木工程学科中能够领导灾后重建的人才严重短缺的问题。在为拉美裔服务的德克萨斯大学阿灵顿分校(UTA)，拉美裔和女性研究生和本科生将参与这个项目的每一步。该项目将使学生能够与城市规划师合作，引导利益相关者参与弱势社区。本项目将通过以下方式解决现有需求激增模型的根本局限性：1)为住房建设成本变化创建非危害性计量经济学基线，2)创建量化灾后建设成本上升的计量经济学方法，3)创建时空计量经济学模型来代表住房重建需求激增，并评估社区的住房重建脆弱性，以及4)量化与灾害相关的政策对住房重建的影响。该项目将在三个关键学科的结合点产生新的知识：住房建设、经济学和建筑环境复原力。这项研究将通过在灾前建筑市场状况和灾后建筑成本上涨之间建立联系来转变现有的建筑需求激增模型。为此，时空计量经济学模型，如空间面板数据模型，将使用过去十年来美国600多个受大规模自然灾害影响的县的数据，以及来自邻近县的数据。这些模型将根据一系列非危险到极端危险条件考虑不同的情况。差异面板数据模型将估计灾难相关政策(从地方政策到联邦政策)的影响。研究团队将与联邦、州和地方政府合作，确定和评估各种与灾害相关的政策。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。