Nelly K. Djuazon, Emmanuel Selorm Tsyawo
arXiv 14 Aug 2024 · Econometrics
arXiv:2408.07842 · PDF · DOI · OpenAlex · Extracted main text
Quantile and Distribution Treatment effects on the Treated (QTT/DTT) for non-continuous outcomes are either not identified or inference thereon is infeasible using existing methods. By introducing functional index parallel trends and no anticipation assumptions, this paper identifies and provides uniform inference procedures for QTT/DTT. The inference procedure applies under both the canonical two-group and staggered treatment designs with balanced panels, unbalanced panels, or repeated cross-sections. Monte Carlo experiments demonstrate the proposed method's robust and competitive performance, while an empirical application illustrates its practical utility.
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| Reference | Intensity | Mentions | Sections | Main text | |
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| 1 | Chernozhukov, Victor, Fernandez-Val, Ivan, Melly, Blaise, Wüthrich,… (2019) Generic inference on quantile and quantile effect functions for discrete outcomes | 0.956 | 8 | 5 | 88% |
| 2 | Di Tella, Rafael, Schargrodsky, Ernesto (2004) Do police reduce crime? Estimates using the allocation of police forces after a terrorist attack | 0.950 | 7 | 4 | 86% |
| 3 | Wooldridge, Jeffrey M (2023) Simple approaches to nonlinear difference-in-differences with panel data | 0.946 | 13 | 5 | 85% |
| 4 | Ghanem, Dalia, Kédagni, Désiré, Mourifié, Ismael (2023) Evaluating the impact of regulatory policies on social welfare in difference-in-difference settings | 0.874 | 8 | 2 | 100% |
| 5 | Gutknecht, Daniel, Liu, Cenchen (2024) Generalized difference-in-differences for ordered choice models: Too many "False Zeros"? | 0.874 | 7 | 2 | 100% |
| 6 | Roth, Jonathan, Sant'Anna, Pedro HC (2023) When is parallel trends sensitive to functional form? | 0.874 | 7 | 2 | 100% |
| 7 | Callaway, Brantly, Li, Tong (2019) Quantile treatment effects in difference in differences models with panel data | 0.874 | 6 | 2 | 100% |
| 8 | Athey, Susan, Imbens, Guido (2006) Identification and inference in nonlinear difference-in-differences models | 0.874 | 5 | 2 | 100% |
| 9 | Chernozhukov, Victor, Fernandez-Val, Ivan, Melly, Blaise (2013) Inference on counterfactual distributions | 0.874 | 5 | 2 | 100% |
| 10 | Yamauchi, Soichiro (2020) Difference-in-differences for ordinal outcomes: Application to the effect of mass shootings on attitudes toward gun control | 0.811 | 4 | 2 | 100% |
Showing the top 10 of 29 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | A Grid-Rate Condition for Valid Uniform Inference | 0.000 | 1 | 1 |