Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/222454 
Erscheinungsjahr: 
2020
Quellenangabe: 
[Journal:] Survey Research Methods [ISSN:] 1864-3361 [Volume:] 14 [Issue:] 2 [Publisher:] European Survey Research Association [Place:] Southampton [Year:] 2020 [Pages:] 153-158
Verlag: 
European Survey Research Association, Southampton
Zusammenfassung: 
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.
Schlagwörter: 
Difference-in-differences
Non-pharmaceutical interventions
COVID-19
Causal inference
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Dokumentart: 
Article
Dokumentversion: 
Published Version

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