arXiv 5 Apr 2022 · Econometrics · publishedThe Review of Economics and Statistics (2025) · 1 citations (OpenAlex)
arXiv:2204.02346 · PDF · DOI · OpenAlex · Extracted main text
A key assumption of the differences-in-differences designs is that the average evolution of untreated potential outcomes is the same across different treatment cohorts: a parallel trends assumption. In this paper, we relax the parallel trend assumption by assuming a latent type variable and developing a type-specific parallel trend assumption. With a finite support assumption on the latent type variable and long pretreatment time periods, we show that an extremum classifier consistently estimates the type assignment. Based on the classification result, we propose a type-specific diff-in-diff estimator for type-specific ATT. By estimating the type-specific ATT, we study heterogeneity in treatment effect, in addition to heterogeneity in baseline outcomes.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Sun and Abraham (2021) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects | 0.950 | 7 | 3 | 86% |
| 2 | De Chaisemartin and d'Haultfoeuille (2020) Two-way fixed effects estimators with heterogeneous treatment effects | 0.928 | 5 | 3 | 80% |
| 3 | Callaway and Sant’Anna (2021) Difference-in-differences with multiple time periods | 0.903 | 19 | 7 | 74% |
| 4 | Lutz (2011) The end of court-ordered desegregation | 0.874 | 14 | 2 | 100% |
| 5 | Janys and Siflinger (2024) Mental health and abortions among young women: Time-varying unobserved heterogeneity, health behaviors, and risky decisions | 0.811 | 4 | 2 | 100% |
| 6 | Borusyak, Jaravel and Spiess (2024) Revisiting event-study designs: robust and efficient estimation | 0.644 | 3 | 2 | 67% |
| 7 | Abadie (2005) Semiparametric difference-in-differences estimators | 0.585 | 3 | 1 | 100% |
| 8 | Roth and Sant'Anna (2023) Efficient estimation for staggered rollout designs | 0.511 | 3 | 2 | 33% |
| 9 | Abadie, Diamond and Hainmueller (2010) Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program | 0.511 | 2 | 2 | 50% |
| 10 | Arkhangelsky, Athey, Hirshberg, Imbens and Wager (2021) Synthetic difference-in-differences | 0.511 | 2 | 2 | 50% |
Showing the top 10 of 27 scored citations.