What type of study is this?

This is a Quantitative Study study.

October 16, 2025Open Access

Conditional Triple Difference-in-Differences

Key Points

Fixing covariate distributions reduces bias in causal estimations, enhancing accuracy in analyses.
By developing a double-robust estimator, the approach can effectively estimate causal effects in varied settings.
This method addresses limitations in standard practices prevalent in empirical research, providing a robust framework.
The applications shown in canonical policy settings underline the method's relevance for practical implications.

Abstract

Triple difference-in-differences designs are widely used to estimate causal effects in empirical work. Surveying the literature, we find that most applications include controls. We show that this standard practice is generally biased for the target causal estimand when covariate distributions differ across groups. To address this, we propose identifying a causal estimand by fixing the covariate distribution to that of one group. We then develop a double-robust estimator and illustrate its application in a canonical policy setting.

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Cite This Study

Dor Leventer (Sat,) studied this question.

synapsesocial.com/papers/68f0d5eb105731330a2b1e76 https://doi.org/https://doi.org/10.48550/arxiv.2502.16126

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