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Treatment-effect heterogeneity and interactive fixed effects: Can we control for too much?

Author

Listed:
  • Murilo Cardoso
  • Bruno Ferman
  • Marcelo Fernandes

Abstract

This paper studies the interactive fixed effects (IFE) estimator in a panel-data setting with heterogeneous treatment effects. We show that, if the treatment-effect heterogeneity admits a linear factor structure, the IFE estimator could fail to recover the average treatment effect on the treated units. The problem arises because the interactive fixed effects absorb the heterogeneity in the treatment effect, creating a \textit{bad-control} problem. With time-invariant factors or unit-invariant loadings in the treatment effect heterogeneity, identification may further break down due to multicollinearity. These problems are not present in alternative estimation methods that exclude treated units in post-treatment periods from the factor estimation.

Suggested Citation

  • Murilo Cardoso & Bruno Ferman & Marcelo Fernandes, 2026. "Treatment-effect heterogeneity and interactive fixed effects: Can we control for too much?," Papers 2604.27187, arXiv.org.
    • Handle: RePEc:arx:papers:2604.27187
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    References listed on IDEAS

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