Keeping Shelters in Place: Understanding the Impacts of Residential Landlord Decision-Making on Post-Disaster Housing Stability

保持住所到位：了解住宅业主决策对灾后住房稳定性的影响

• 批准号: 2139816
• 负责人: Jane Rongerude
• 金额: $ 63.54万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-11-01 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2139816&HistoricalAwards=false
• 关键词: Keeping; Shelters; Place; Understanding; Impacts

This research is responding to the local threats to rental housing security that emerged during the COVID-19 pandemic. Rental housing occupies a significant portion of the housing stock in US metropolitan areas, yet researchers know very little about the specific characteristics of the institutional and non-institutional entities that hold titles to those properties and determine housing supply, rents, and the conditions of both buildings and units. To further complicate this scenario, regulatory environments and rental housing market dynamics vary greatly across space, both within and between metropolitan regions. Resiliency, the ability to withstand and recover from a disaster or a shock, is shaped by the conditions of the local housing market and the associated regulatory environment. However, it is also shaped by the behaviors of the landlord population operating within that milieu. In the absence of existing knowledge about landlord characteristics, behaviors, and needs, cities and policy makers responding to disasters are left guessing how to stabilize their rental markets, keep renters housed, deliver meaningful assistance to property owners, and plan for an effective post-disaster recovery. This study contributes to the progress of science by investigating rental property owner characteristics and identifying meaningful rental owner categories as they relate to disaster and post-disaster decision-making. It contributes to the national health, prosperity and welfare by linking that knowledge to disaster-related rental housing outcomes in specific places. The COVID-19 pandemic has demonstrated that the security of the rental housing market is intertwined with a landlord’s ability to tackle financial challenges. The decisions that landlords make in the midst of a disaster affect not only their tenants’ ability to remain housed, but the ability of the city to respond to and recover from the event and ensure future housing stability.The central hypothesis of this study is that when responding to disasters, non-institutional rental property owners make property and investment decisions that accelerate ownership consolidation and reduce post-disaster housing security within communities. The research is structured as a longitudinal study using an innovative, convergent approach that brings together social science and data science in order to create new datasets and tools for data analysis. It fills a major gap in existing knowledge by investigating landlord decision-making across the stages of the disaster management cycle and identifying meaningful categories of non-institutional rental property owners based on landlord characteristics. This study sets out to answer not just who landlords are, but how they respond to disasters and how disaster-induced changes in the landlord population might continue to affect the built environment of cities and communities into the future. There are two nested research efforts within this proposal: to understand landlord characteristics and decision-making within the context of the post-pandemic recovery and potential future shocks or disasters; and, through data science approaches, to identify and characterize the landlord population and the potential value of better data utilization for promoting rental housing security during local recovery from hazard-related shocks and stresses. The overall project goals to improve housing outcomes within local disaster recovery efforts draw from the domain of social science including planning, sociology, economics, and finance. The project goals to create tools that improve the local institutional capacity for identifying and communicating with landlords rely on the domain of data science research. This project’s integrative methodology strengthens the capacity of each domain, generating an innovative approach where social science research is able to resolve the enduring problem of landlord invisibility and the data science techniques are refined through their application to real world problems. The unit of analysis for this study is the rental property owner, specifically non-institutional investors, in nine mid-sized US cities. These cites, though of similar size, have varied housing stocks, socioeconomic characteristics, and political orientations. They also provided unique state and local responses to the COVID housing crisis. Five of the cities are located in states that are part of the Gulf Coast region. All have either been recently affected by hazard-related disasters or are at high risk of experiencing a disaster. This chronological range of disaster experience and recovery will allow the tracking of landlord perspectives across the disaster management cycle.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.

这项研究是为了应对COVID-19大流行期间出现的对出租房屋安全的本地威胁。租赁住房占据了美国大都市地区住房存量的很大一部分，但研究人员对持有这些财产所有权并决定住房供应，租金以及建筑物和单位条件的机构和非机构实体的具体特征知之甚少。为了使这种情况进一步复杂化，监管环境和租赁住房市场动态在大都市地区内部和之间的空间差异很大。复原力，即承受灾难或冲击并从中恢复的能力，取决于当地住房市场的条件和相关的监管环境。然而，它也是由地主人口的行为在这种环境中运作。在缺乏关于房东特征、行为和需求的现有知识的情况下，应对灾害的城市和政策制定者只能猜测如何稳定租赁市场，让租房者有房住，为业主提供有意义的援助，并计划有效的灾后恢复。这项研究有助于科学的进步，通过调查租赁业主的特点，并确定有意义的租赁业主类别，因为它们涉及到灾害和灾后决策。它通过将这些知识与特定地方与灾害有关的租赁住房成果联系起来，为国家的健康、繁荣和福利做出贡献。COVID-19疫情表明，租赁住房市场的安全与业主应对财务挑战的能力息息相关。房东在灾难中做出的决定不仅影响租户的居住能力，而且影响城市应对和恢复事件的能力，并确保未来的住房稳定性。本研究的中心假设是，在应对灾难时，非机构出租物业业主作出物业和投资决策，加速所有权整合，并减少后，社区内的灾后住房保障。该研究是一项纵向研究，采用创新的融合方法，将社会科学和数据科学结合在一起，以创建新的数据集和数据分析工具。它通过调查灾难管理周期各个阶段的房东决策并根据房东特征识别有意义的非机构出租物业业主类别，填补了现有知识的重大空白。这项研究不仅要回答房东是谁，还要回答他们如何应对灾害，以及灾害引起的房东人口变化如何继续影响未来城市和社区的建筑环境。该提案中有两项嵌套的研究工作：在大流行后恢复和未来潜在冲击或灾害的背景下了解房东的特征和决策;通过数据科学方法，确定和描述房东人口以及更好地利用数据的潜在价值，以促进当地从灾害相关冲击和压力中恢复期间的租赁住房安全。在当地灾后恢复工作中改善住房成果的总体项目目标来自社会科学领域，包括规划、社会学、经济学和金融学。该项目的目标是创建工具，提高当地机构识别和与房东沟通的能力，这依赖于数据科学研究领域。该项目的综合方法加强了每个领域的能力，产生了一种创新的方法，使社会科学研究能够解决房东隐形的持久问题，并通过将其应用于真实的世界问题来改进数据科学技术。本研究的分析单位是美国九个中等城市的出租物业所有者，特别是非机构投资者。这些城市虽然规模相似，但住房存量、社会经济特征和政治取向各不相同。他们还提供了独特的国家和地方应对COVID住房危机。其中五个城市位于墨西哥湾沿岸地区的一部分。所有这些国家或最近受到与危害有关的灾害的影响，或面临着遭受灾害的高风险。这个灾难经验和恢复的时间范围将允许在整个灾难管理周期中跟踪房东的观点。这个奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。