Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/324005 
Year of Publication: 
2025
Citation: 
[Journal:] Journal of Causal Inference [ISSN:] 2193-3685 [Volume:] 13 [Issue:] 1 [Article No.:] 20240040 [Publisher:] De Gruyter Brill [Place:] Berlin [Year:] 2025 [Pages:] 1-7
Publisher: 
De Gruyter Brill, Berlin
Abstract: 
Fixed effects estimation, with linear controls for stratum membership, is often used to estimate treatment effects when assignment propensities differ across strata. In the presence of heterogeneity in treatment effects across strata, this estimator does not target the average treatment effect, however. Indeed, the implied estimand can range anywhere from the lowest to the highest stratum-level average effect. To facilitate the interpretation of results using this approach, I establish that if stratum-level average effects are monotonic in the shares assigned to treatment, then the fixed effects estimand lies between the average treatment effect for the treated and the average treatment effect for the controls.
Subjects: 
causal inference
least squares
fixed effects
heterogeneous assignment propensities
bias
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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