A Joint Analysis of Sensitivity to Anticipation and Parallel Trends Violations
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866917302614622208 |
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| author | Fenaroli, Gianna |
| author_facet | Fenaroli, Gianna |
| contents | Two key identifying assumptions used to justify difference-in-differences are parallel trends and no anticipation, yet both may fail in practice. I propose a class of assumptions on anticipation and derive closed-form, sharp bounds on the average treatment effect on the treated while simultaneously relaxing parallel trends. Deviations from both assumptions are jointly disciplined using observed pre-trends. When some anticipation is imposed, the identified set under joint deviations can be shorter than under parallel trends violations alone. These bounds inform a sensitivity analysis assessing the robustness of qualitative conclusions to anticipation and parallel trends violations. I illustrate with an empirical application. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2603_00868 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Joint Analysis of Sensitivity to Anticipation and Parallel Trends Violations Fenaroli, Gianna Econometrics Two key identifying assumptions used to justify difference-in-differences are parallel trends and no anticipation, yet both may fail in practice. I propose a class of assumptions on anticipation and derive closed-form, sharp bounds on the average treatment effect on the treated while simultaneously relaxing parallel trends. Deviations from both assumptions are jointly disciplined using observed pre-trends. When some anticipation is imposed, the identified set under joint deviations can be shorter than under parallel trends violations alone. These bounds inform a sensitivity analysis assessing the robustness of qualitative conclusions to anticipation and parallel trends violations. I illustrate with an empirical application. |
| title | A Joint Analysis of Sensitivity to Anticipation and Parallel Trends Violations |
| topic | Econometrics |
| url | https://arxiv.org/abs/2603.00868 |