Using Difference-in-Differences to Identify Causal Effects of COVID-19 Policies

Policymakers have implemented a wide range of non-pharmaceutical interventions to fight the spread of COVID-19. Variation in policies across jurisdictions and over time strongly suggests a difference-in-differences (DD) research design to estimate causal effects of counter-COVID measures. We discuss...

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Bibliographic Details
Published inSurvey research methods Vol. 14; no. 2; pp. 153 - 158
Main Authors Goodman-Bacon, Andrew, Marcus, Jan
Format Journal Article
LanguageEnglish
Published Southampton European Survey Research Association 01.01.2020
Subjects
Causal inference
COVID-19
Difference-in-differences
difference-in-differences; non-pharmaceutical interventions; COVID-19; causal inference
Non-pharmaceutical interventions
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Summary:Policymakers have implemented a wide range of non-pharmaceutical interventions to fight the spread of COVID-19. Variation in policies across jurisdictions and over time strongly suggests a difference-in-differences (DD) research design to estimate causal effects of counter-COVID measures. We discuss threats to the validity of these DD designs and make recommendations about how researchers can avoid bias, interpret results accurately, and provide sound guidance to policymakers seeking to protect public health and facilitate an eventual economic recovery.
ISSN:1864-3361
1864-3361
DOI:10.18148/srm/2020.v14i2.7723