论文标题
在大流行中评估政策：界限政策效应与非随机丢失的数据
Evaluating Policies Early in a Pandemic: Bounding Policy Effects with Nonrandomly Missing Data
论文作者
论文摘要
在Covid-19-19大流行的早期，国家和地方政府提出了许多政策，以打击Covid-19的传播。在本文中，我们提出了一种新方法来限制此类早期政策对COVID-19案例和其他结果的影响，同时处理（i）（i）（i）COVID-19的可用性有限，（ii）COVID-19的可用性有限，（ii）COVID-19的差异性可用性，以及（III）对个人进行测试的资格要求。我们使用我们的方法研究田纳西州在大流行中早期进行COVID-19测试的影响，并发现该政策减少了Covid-19案件。
During the early part of the Covid-19 pandemic, national and local governments introduced a number of policies to combat the spread of Covid-19. In this paper, we propose a new approach to bound the effects of such early-pandemic policies on Covid-19 cases and other outcomes while dealing with complications arising from (i) limited availability of Covid-19 tests, (ii) differential availability of Covid-19 tests across locations, and (iii) eligibility requirements for individuals to be tested. We use our approach study the effects of Tennessee's expansion of Covid-19 testing early in the pandemic and find that the policy decreased Covid-19 cases.
