RAPID: Income and Poverty in the COVID-19 Pandemic

摘要在新冠肺炎疫情爆发的九周内，有3900万人申请失业保险，而2020年第一季度的国内生产总值下降了4.8%。联邦政府的回应是史无前例的刺激立法，承诺投入超过2万亿美元来应对疫情的影响。有效地瞄准和调整政府的财政应对措施，需要按人口群体和地理位置及时跟踪收入和贫困的变化，而这方面的能力极其有限。对2020年收入和贫困的官方估计要到2021年9月才能公布。该项目直接回应了这一需要，即开发新的程序，通过及时和准确地提供关于当前大流行病对收入和贫困的影响的信息，帮助应对新冠肺炎大流行病的经济影响，以便将资源投向受影响最严重的人。该项目旨在使用具有代表性的大样本美国家庭的高频数据，在仅滞后几周的情况下构建收入分配和贫困的新衡量标准。该项目将对促进经济学和相关社会科学领域的基本知识产生直接影响，并通过对收入和贫困进行新的、接近实时的估计，为决策者提供工具。该项目将通过将依赖于这些数据的历史估计与更广泛使用的收入和消费数据估计进行比较，来验证新的、及时的收入衡量标准。重要的是，这些验证工作将利用新的数据，将调查数据与个人层面的税收和项目数据联系起来。这一验证将帮助研究人员理解使用更及时的收入数据来研究经济福祉变化的优势和局限性。该项目还将解决有关大型经济冲击的影响和调查收入衡量的关键问题，这两个因素都是许多经济研究的关键要素。该奖项反映了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。

AbstractIn nine weeks at the start of the COVID-19 pandemic 39 million people filed for unemployment insurance, while GDP for the first quarter of 2020 was down 4.8%. The federal government responded with unprecedented stimulus legislation that committed more than two trillion dollars to countering the effects of the pandemic. Effectively targeting and calibrating the government's fiscal response requires tracking changes in income and poverty by demographic group and geography in a timely way, which there is extremely limited ability to do. Official estimates of income and poverty for 2020 will not be available until September of 2021. This project responds directly to this need to develop new processes to help address the economic impact of the COVID-19 pandemic by providing timely and accurate information on the impact of the current pandemic on income and poverty to inform the targeting of resources to those most affected. The project aims to construct new measures of the income distribution and poverty with a lag of only a few weeks using high frequency data for a large, representative sample of U.S. families. This project will have immediate impact in advancing basic knowledge in the fields of economics and related social sciences and providing tools for policy makers by constructing new, near real-time estimates of income and poverty. The project will validate new, timely measure of income by comparing historical estimates that rely on these data to estimates from data on income and consumption that have been used much more broadly. Importantly, these validation exercises will utilize new data that links survey data to tax and program data at the individual level. The validation will help researchers understand the advantages and limitations of using more timely income data to study changes in economic well-being. This project will also address key questions regarding the impacts of large economic shocks and survey income measurement, both critical elements of much economic research.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.