Treatment-effect heterogeneity and interactive fixed effects: Can we control for too much?
Fuente:
arXiv
Saved in:
| Main Authors: | Cardoso, Murilo, Ferman, Bruno, Fernandes, Marcelo |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On the relationship between prediction intervals, tests of sharp nulls and inference on realized treatment effects in settings with few treated units
by: Alvarez, Luis, et al.
Published: (2025)
by: Alvarez, Luis, et al.
Published: (2025)
On the Use of Design-Based Simulations
by: Ferman, Bruno
Published: (2026)
by: Ferman, Bruno
Published: (2026)
Assessing Inference Methods
by: Ferman, Bruno
Published: (2019)
by: Ferman, Bruno
Published: (2019)
How much is too much? Measuring divergence from Benford's Law with the Equivalent Contamination Proportion (ECP)
by: Cano-Rodriguez, Manuel
Published: (2025)
by: Cano-Rodriguez, Manuel
Published: (2025)
Dynamic LATEs with a Static Instrument
by: Ferman, Bruno, et al.
Published: (2023)
by: Ferman, Bruno, et al.
Published: (2023)
When can we get away with using the two-way fixed effects regression?
by: Lal, Apoorva
Published: (2025)
by: Lal, Apoorva
Published: (2025)
Estimation of random coefficients logit demand models with interactive fixed effects
by: Moon, Hyungsik Roger, et al.
Published: (2026)
by: Moon, Hyungsik Roger, et al.
Published: (2026)
Analysis of interactive fixed effects dynamic linear panel regression with measurement error
by: Lee, Nayoung, et al.
Published: (2026)
by: Lee, Nayoung, et al.
Published: (2026)
Specification testing with grouped fixed effects
by: Pigini, Claudia, et al.
Published: (2023)
by: Pigini, Claudia, et al.
Published: (2023)
A projection based approach for interactive fixed effects panel data models
by: Keilbar, Georg, et al.
Published: (2022)
by: Keilbar, Georg, et al.
Published: (2022)
Linear estimations of dynamic fixed effects logit models only with time effects
by: Kitazawa, Yoshitsugu
Published: (2026)
by: Kitazawa, Yoshitsugu
Published: (2026)
Grouped fixed effects regularization for binary choice models
by: Pigini, Claudia, et al.
Published: (2025)
by: Pigini, Claudia, et al.
Published: (2025)
A quantile-based nonadditive fixed effects model
by: Liu, Xin
Published: (2024)
by: Liu, Xin
Published: (2024)
On the falsification of instrumental variable models for heterogeneous treatment effects
by: Miranda, Ricardo E.
Published: (2026)
by: Miranda, Ricardo E.
Published: (2026)
Partial Identification under Stratified Randomization
by: Ferman, Bruno, et al.
Published: (2026)
by: Ferman, Bruno, et al.
Published: (2026)
Binary choice logit models with general fixed effects for panel and network data
by: Dano, Kevin, et al.
Published: (2025)
by: Dano, Kevin, et al.
Published: (2025)
A jackknife bias correction for nonlinear network data models with fixed effects
by: Hughes, David W.
Published: (2022)
by: Hughes, David W.
Published: (2022)
Estimating interaction effects with panel data
by: Muris, Chris, et al.
Published: (2022)
by: Muris, Chris, et al.
Published: (2022)
Two-way fixed effects instrumental variable regressions in staggered DID-IV designs
by: Miyaji, Sho
Published: (2024)
by: Miyaji, Sho
Published: (2024)
Identification and estimation of treatment effects in a linear factor model with fixed number of time periods
by: Fusejima, Koki, et al.
Published: (2025)
by: Fusejima, Koki, et al.
Published: (2025)
Root-n-consistent Conditional ML estimation of dynamic panel logit models with fixed effects
by: Kruiniger, Hugo
Published: (2021)
by: Kruiniger, Hugo
Published: (2021)
The heterogeneous role of party affiliation in the runner‐up effect
by: Umair Khalil, et al.
Published: (2024)
by: Umair Khalil, et al.
Published: (2024)
Instrumental Variables with Time-Varying Exposure: New Estimates of Revascularization Effects on Quality of Life
by: Angrist, Joshua D., et al.
Published: (2025)
by: Angrist, Joshua D., et al.
Published: (2025)
Global identification of dynamic panel models with interactive effects
by: Bai, Jushan, et al.
Published: (2025)
by: Bai, Jushan, et al.
Published: (2025)
Comment on "Generic machine learning inference on heterogeneous treatment effects in randomized experiments."
by: Imai, Kosuke, et al.
Published: (2025)
by: Imai, Kosuke, et al.
Published: (2025)
Treatment effects at the margin: Everyone is marginal
by: Deng, Haotian
Published: (2025)
by: Deng, Haotian
Published: (2025)
The heterogeneous causal effects of the EU's Cohesion Fund
by: Alexopoulos, Angelos, et al.
Published: (2025)
by: Alexopoulos, Angelos, et al.
Published: (2025)
New possibilities in identification of binary choice models with fixed effects
by: Zhu, Yinchu
Published: (2022)
by: Zhu, Yinchu
Published: (2022)
Bayesian inference for dynamic spatial quantile models with interactive effects
by: Ando, Tomohiro, et al.
Published: (2025)
by: Ando, Tomohiro, et al.
Published: (2025)
Efficiency of QMLE for dynamic panel data models with interactive effects
by: Bai, Jushan
Published: (2023)
by: Bai, Jushan
Published: (2023)
Estimating treatment-effect heterogeneity across sites, in multi-site randomized experiments with few units per site
by: de Chaisemartin, Clément, et al.
Published: (2024)
by: de Chaisemartin, Clément, et al.
Published: (2024)
Predicting the Distribution of Treatment Effects: A Covariate-Adjustment Approach
by: Fava, Bruno
Published: (2024)
by: Fava, Bruno
Published: (2024)
Debiasing and $t$-tests for synthetic control inference on average causal effects
by: Chernozhukov, Victor, et al.
Published: (2018)
by: Chernozhukov, Victor, et al.
Published: (2018)
Functional effects models: Accounting for preference heterogeneity in panel data with machine learning
by: Salvadé, Nicolas, et al.
Published: (2025)
by: Salvadé, Nicolas, et al.
Published: (2025)
Axiomatic modeling of fixed proportion technologies
by: Zhou, Xun, et al.
Published: (2024)
by: Zhou, Xun, et al.
Published: (2024)
Prediction intervals for economic fixed-event forecasts
by: Krüger, Fabian, et al.
Published: (2022)
by: Krüger, Fabian, et al.
Published: (2022)
Peer effect analysis with latent processes
by: Starck, Vincent
Published: (2025)
by: Starck, Vincent
Published: (2025)
Heterogeneity in peer effects for binary outcomes
by: Lambotte, Mathieu
Published: (2025)
by: Lambotte, Mathieu
Published: (2025)
Inference after discretizing time-varying unobserved heterogeneity
by: Beyhum, Jad, et al.
Published: (2024)
by: Beyhum, Jad, et al.
Published: (2024)
Your Season of Birth Tells much of you and your Background European Edition
by: Domenico Depalo
Published: (2025)
by: Domenico Depalo
Published: (2025)
Similar Items
-
On the relationship between prediction intervals, tests of sharp nulls and inference on realized treatment effects in settings with few treated units
by: Alvarez, Luis, et al.
Published: (2025) -
On the Use of Design-Based Simulations
by: Ferman, Bruno
Published: (2026) -
Assessing Inference Methods
by: Ferman, Bruno
Published: (2019) -
How much is too much? Measuring divergence from Benford's Law with the Equivalent Contamination Proportion (ECP)
by: Cano-Rodriguez, Manuel
Published: (2025) -
Dynamic LATEs with a Static Instrument
by: Ferman, Bruno, et al.
Published: (2023)