新冠疫情的经济影响：来自利用私营部门数据构建的新公共数据库的证据
The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data
Quarterly Journal of Economics · 2023 · [{"name": "Raj Chetty", "affiliation": ["Harvard University Press"]}, {"name": "John N. Friedman", "affiliation": ["John Brown University"]}, {"name": "Michael Stepner", "affiliation": ["University of Toronto"]}, {"name": "Opportunity Insights Team", "affiliation": []}, {"name": "Hamidah Alatas", "affiliation": []}, {"name": "Camille Baker", "affiliation": []}, {"name": "Harvey Barnhard", "affiliation": []}, {"name": "Matthew R. Bell", "affiliation": []}, {"name": "Gregory Alan Bruich", "affiliation": []}, {"name": "Tina Chelidze", "affiliation": []}, {"name": "LK Chu", "affiliation": []}, {"name": "Westley Cineus", "affiliation": []}, {"name": "Sebi Devlin-Foltz", "affiliation": ["University of Toronto"]}, {"name": "Michael Droste", "affiliation": []}, {"name": "Dhruv Gaur", "affiliation": []}, {"name": "Federico Zertuche González", "affiliation": []}, {"name": "Rayshauna Gray", "affiliation": []}, {"name": "Abigail Hiller", "affiliation": []}, {"name": "Matthew Jacob", "affiliation": []}, {"name": "Tyler Jacobson", "affiliation": []}, {"name": "Margaret Kallus", "affiliation": []}, {"name": "Fiona Kastel", "affiliation": []}, {"name": "Laura Kincaide", "affiliation": []}, {"name": "Caitlin Kupsc", "affiliation": []}, {"name": "Sarah LaBauve", "affiliation": []}, {"name": "Lucía Martínez Lamas", "affiliation": []}, {"name": "Maddie Marino", "affiliation": []}, {"name": "Kai Matheson", "affiliation": []}, {"name": "Jared Miller", "affiliation": []}, {"name": "Christian Mott", "affiliation": []}, {"name": "Kate Musen", "affiliation": []}, {"name": "Danny Onorato", "affiliation": []}, {"name": "Sarah Oppenheimer", "affiliation": []}, {"name": "Trina Ott", "affiliation": []}, {"name": "Lynn Overmann", "affiliation": []}, {"name": "Max Pienkny", "affiliation": []}, {"name": "Jeremiah Prince", "affiliation": []}, {"name": "Sebastian Puerta", "affiliation": []}, {"name": "Daniel A. Reuter", "affiliation": []}, {"name": "Peter Ruhm", "affiliation": []}, {"name": "Tom Rutter", "affiliation": []}, {"name": "Emanuel Schertz", "affiliation": []}, {"name": "Shannon Felton Spence", "affiliation": []}, {"name": "Krista Stapleford", "affiliation": []}, {"name": "Kamelia Stavreva", "affiliation": []}, {"name": "Ceci Steyn", "affiliation": []}, {"name": "James Stratton", "affiliation": []}, {"name": "Clare Suter", "affiliation": []}, {"name": "Elizabeth Thach", "affiliation": []}, {"name": "Nicolaj Thor", "affiliation": []}, {"name": "Amanda Wahlers", "affiliation": []}, {"name": "Kristen Watkins", "affiliation": []}, {"name": "A.K. Williams", "affiliation": []}, {"name": "David Williams", "affiliation": []}, {"name": "Chase Williamson", "affiliation": []}, {"name": "Shady Yassin", "affiliation": []}, {"name": "Ruby Zhang", "affiliation": []}, {"name": "Aiyun Zheng", "affiliation": []}]
中文摘要
我们利用私营企业的匿名化数据，构建了一个公开可用的数据库，以细粒度、实时的方式追踪美国的经济活动。我们按县、行业和收入群体分类，报告消费者支出、企业营收、招聘信息和就业率的周度统计数据。利用这些公开数据，我们通过分析新冠疫情影响在不同群体间的异质性，展示了疫情如何影响经济。2020年3月，高收入群体大幅削减支出，尤其是在需要面对面互动的行业。这一支出削减使富裕、人口密集地区小企业的营收大幅下降。这些企业解雇了大量员工，导致广泛的就业损失，其中此类地区的低工资劳动者受冲击尤为严重。高工资劳动者经历了一场仅持续数周的V形衰退，而低工资劳动者的就业损失则规模更大、持续时间更长。尽管到2021年12月消费者支出和招聘信息已完全恢复，但在最初受创最严重的地区，低工资岗位的就业率依然低迷，这表明劳动需求的暂时性下降导致了劳动供给的持久性减少。基于这一诊断性分析，我们评估了旨在遏制经济活动螺旋式下滑的财政刺激政策的效果。现金刺激补助在疫情初期使支出大幅增加，但在疫情后期引发的反应明显减弱，尤其是在高收入家庭中。基于实时数据的边际消费倾向估计，比历史估计值更能准确预测后续各轮刺激补助的影响。总体而言，我们的研究结果表明，财政政策能够遏制消费者支出与就业损失的次生下降，但当消费者支出的初始冲击源于健康方面的担忧时，财政政策无法恢复充分就业。更广泛而言，我们的分析表明，利用私营部门数据构建的公共统计数据可以支持大量研究与实时政策分析，为实证宏观经济学提供了一种新工具。
Abstract
We build a publicly available database that tracks economic activity in the United States at a granular level in real time using anonymized data from private companies. We report weekly statistics on consumer spending, business revenues, job postings, and employment rates disaggregated by county, sector, and income group. Using the publicly available data, we show how the COVID-19 pandemic affected the economy by analyzing heterogeneity in its effects across subgroups. High-income individuals reduced spending sharply in March 2020, particularly in sectors that require in-person interaction. This reduction in spending greatly reduced the revenues of small businesses in affluent, dense areas. Those businesses laid off many of their employees, leading to widespread job losses, especially among low-wage workers in such areas. High-wage workers experienced a V-shaped recession that lasted a few weeks, whereas low-wage workers experienced much larger, more persistent job losses. Even though consumer spending and job postings had recovered fully by December 2021, employment rates in low-wage jobs remained depressed in areas that were initially hard hit, indicating that the temporary fall in labor demand led to a persistent reduction in labor supply. Building on this diagnostic analysis, we evaluate the effects of fiscal stimulus policies designed to stem the downward spiral in economic activity. Cash stimulus payments led to sharp increases in spending early in the pandemic, but much smaller responses later in the pandemic, especially for high-income households. Real-time estimates of marginal propensities to consume provided better forecasts of the impacts of subsequent rounds of stimulus payments than historical estimates. Overall, our findings suggest that fiscal policies can stem secondary declines in consumer spending and job losses, but cannot restore full employment when the initial shock to consumer spending arises from health concerns. More broadly, our analysis demonstrates how public statistics constructed from private sector data can support many research and real-time policy analyses, providing a new tool for empirical macroeconomics.