Evaluating Rental Relief During the COVID-19 Pandemic

项目摘要 2019冠状病毒病疫情引发了突如其来的严重经济冲击，打击了低收入家庭 和有色人种最为严重。许多美国租房家庭已经承受了住房成本的压力， 导致人们担心会出现住房不稳定和驱逐潮，并对其他形式的困难产生相关影响 例如粮食不安全。考虑到住房不稳定和驱逐是健康和发展的关键社会决定因素， 健康差距、心理健康的溢出效应也在预料之中。2020 - 2021年，联邦政府 为紧急租赁援助计划（ERAP）拨款466亿美元，以支持各州， 县，市政府在解决租赁住房困难。ERAP的大部分资金必须是 用于租金和拖欠租金的财政援助，公用事业援助和公用事业欠款，以及一套有限的 因疫情而产生的其他与住房相关的支出（例如，搬迁费用）;国家和 另外，在资金分配方面，市政当局有很大的灵活性。本项目谋求 对ERAP政策进行首次系统和严格的评估。 这项研究的首要目标是仔细记录州和地方ERAP设计的变化， 包括通过和实施各种规则的时间，并评估不同规则的影响， 使用利用地理差异的准实验方法的ERAP方法 和跨时间。这项研究有三个主要目标。首先，我们将创建一个独特的，公开访问的，用户- 租金减免政策数据库（RRPD）是一个友好的数据集，它跟踪地方、州和国家的ERAP政策。 其次，我们将把RRPD与来自全国代表性家庭的家庭调查数据合并， 美国人口普查局在整个大流行期间进行的脉搏调查。脉搏包括以下指标 住房不稳定、食物不足和其他物质困难以及精神健康。我们将分析这些 数据使用逻辑回归模型与状态和年份指标，这将使我们能够估计因果关系 ERAP政策对租房家庭关键结果的影响。第三，我们将RRPD与每周 在美国31个城市地区的人口普查区或邮政编码级别的驱逐申请计数。采用 复杂的技术-多层次零膨胀负二项模型-我们将评估的影响， 州和地方ERAP关于驱逐申请率的政策。这项工作的成果将增加 了解COVID-19政策的有效性和不公平的趋势，并作为一个蓝图， 稳定日益不稳定的出租住房所需的政策和公共卫生举措。

PROJECT SUMMARY The COVID-19 pandemic triggered a sudden and severe economic shock which hit low-income households and households of color most severely. Many U.S. renter households were already housing-cost stressed, leading to fears of a wave of housing instability and evictions and related effects on other forms of hardship such as food insecurity. Given that housing instability and eviction are key social determinants of health and health disparities, overflow effects on mental health were also expected. In 2020-2021 the federal government allocated $46.6 billion in funding for the Emergency Rental Assistance Program (ERAP) to support state, county, and municipal governments in addressing rental housing difficulties. The bulk of ERAP funds must be used for financial assistance for rent and rent arrears, utility assistance and utility arrears, and a limited set of other housing-related expenses arising from the pandemic (e.g., relocation expenses); states and municipalities were otherwise given extensive flexibility over the distribution of funds. This project seeks to provide the first systematic and rigorous evaluation of the ERAP policy. The overarching goals of this study are to carefully document variation in state and local ERAP design, including timing of adoption and implementation of various rules, and to evaluate the effects of different approaches to ERAP using quasi-experimental methods that take advantage of differences across geography and across time. This study has three key aims. First, we will create a unique, publicly-accessible, and user- friendly dataset that tracks local, state, and national ERAP policies, the Rental Relief Policy Database (RRPD). Second, we will merge the RRPD with household survey data from the nationally representative Household Pulse Survey fielded by the U.S. Census Bureau throughout the pandemic. Pulse includes measures of housing instability, food insufficiency and other material hardships, and mental health. We will analyze these data using logistic regression models with state and year indicators which will allow us to estimate the causal effect of ERAP policies on critical outcomes in renter households. Third, we will link the RRPD to weekly counts of eviction filings at the Census tract or ZIP code level in 31 U.S. municipal areas. Employing sophisticated techniques—multilevel zero-inflated negative binomial models—we will evaluate the effects of state and local ERAP policies on the rate of eviction filings. Results from this work will both increase understanding of COVID-19 policy effectiveness and trends in inequities, and serve as a blueprint for additional policy and public health initiatives necessary to stabilize increasingly precarious rental housing.