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Conditional Triple Difference-in-Differences

Dor Leventer

arXiv 22 Feb 2025 · Econometrics

arXiv:2502.16126 · PDF · DOI · OpenAlex · Extracted main text

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.

Citation extraction

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appendix boundary found by appendix_command · 68% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Callaway, Brantly, Sant’Anna, Pedro HC (2021) Difference-in-differences with multiple time periods1.00074100%
2Sant’Anna, Pedro HC, Zhao, Jun (2020) Doubly robust difference-in-differences estimators1.00073100%
3Cunningham, Scott (2021) Causal inference: The mixtape0.92844100%
4Kleven, Henrik, Landais, Camille (2019) Children and gender inequality: Evidence from Denmark0.92843100%
5Card, David, Krueger, Alan B (1993) Minimum wages and employment: A case study of the fast food industry in New Jersey and Pennsylvania0.73732100%
6Chang, Neng-Chieh (2020) Double/debiased machine learning for difference-in-differences models0.73732100%
7Muralidharan, Karthik, Prakash, Nishith (2017) Cycling to school: Increasing secondary school enrollment for girls in India0.73732100%
8Olden, Andreas (2022) The triple difference estimator0.73732100%
9Angrist, Joshua D, Pischke, Jörn-Steffen (2009) Mostly harmless econometrics: An empiricist's companion0.64422100%
10Goldin, Claudia, Olivetti, Claudia (2013) Shocking labor supply: A reassessment of the role of World War II on women's labor supply0.51121100%

Showing the top 10 of 18 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Three’s a crowd: Identification challenges in the triple difference model with spillover effects0.40511
2Identification of Child Penalties0.00011