Evaluating Policies Early in a Pandemic: Bounding Policy Effects with Nonrandomly Missing Data

• 成果类型: Article
• 署名作者: Callaway, Brantly; Li, Tong
• 署名单位: University System of Georgia; University of Georgia; Vanderbilt University
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest_a_01306
• 发表日期: 2025-05
• 页码: 803-819
• 关键词: partial identification; Double Robustness; PREVALENCE; tests

摘要

During the early part of the COVID-19 pandemic, national andlocal governments introduced a number of policies to combat the spread ofCOVID-19. In this paper, we propose a new approach to bound the effectsof such early-pandemic policies on COVID-19 cases and other outcomeswhile dealing with complications arising from (i) limited availability ofCOVID-19 tests, (ii) differential availability of COVID-19 tests acrosslocations, and (iii) eligibility requirements for individuals to be tested. Weuse our approach study the effects of Tennessee's expansion of COVID-19testing early in the pandemic and find that the policy decreased COVID-19cases.