Analyzing Heterogeneous Treatment Effects and Causal Mechanisms in Social Science Research
By
JIAWEI FU* Affiliation: Duke University , United States
Summary
This article from the American Political Science Review examines how social scientists make causal claims about treatment effects, specifically focusing on heterogeneous treatment effects (HTEs) as a method for understanding causal mechanisms. It uses examples such as an outreach program increasing COVID-19 reporting rates by building trust in government, and local media increasing political knowledge through news coverage rather than advertising. The piece provides a rigorous, in-depth academic analysis of methodological approaches to identifying and interpreting heterogeneous treatment effects in causal inference.
Source
Twitter / XAnalyzing Heterogeneous Treatment Effects and Causal Mechanisms in Social Science Researchdoi.orgKey quotes
· 4 pulledSocial scientists often make claims about how or why a treatment affects a given outcome.
Researchers might tell us, for example, not only that an outreach program increased COVID-19 reporting rates, but that it did so by building trust in government.
Or researchers might claim that access to local media increases knowledge of local politics because of the content of news coverage, not because of local political advertising.
Claims of this type are often made on the basis of heterogeneous treatment effects (HTEs): the effect of the outreach program on COVID-19 reporting is larger in places t
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