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Erscheinungsjahr: 
2025
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[Journal:] Journal of Causal Inference [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
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De Gruyter Brill, Berlin
Zusammenfassung: 
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.
Schlagwörter: 
causal inference
least squares
fixed effects
heterogeneous assignment propensities
bias
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