Bounds on the fixed effects estimand in the presence of heterogeneous assignment propensities

Humphreys Macartan ()
Additional contact information
Humphreys Macartan: WZB, Berlin, Germany

Journal of Causal Inference, 2025, vol. 13, issue 1, 7

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.

Keywords: causal inference; least squares; fixed effects; heterogeneous assignment propensities; bias (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/jci-2024-0040 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:causin:v:13:y:2025:i:1:p:7:n:1001

DOI: 10.1515/jci-2024-0040

Access Statistics for this article

Journal of Causal Inference is currently edited by Elias Bareinboim, Jin Tian and Iván Díaz

More articles in Journal of Causal Inference from De Gruyter
Bibliographic data for series maintained by Peter Golla ().