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https://doi.org/10.1515/jci-2024-0040

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

[journal article]

Humphreys, Macartan

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, howe... view more

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.... view less

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Free Keywords
bias; causal inference; fixed effects; heterogeneous assignment propensities; least squares

Document language
English

Publication Year
2025

Page/Pages
p. 1-7

Journal
Journal of Causal Inference, 13 (2025) 1

ISSN
2193-3685

Status
Published Version; peer reviewed

Licence
Creative Commons - Attribution 4.0


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.