Fangzhou Yu
arXiv 8 Sep 2026 · Econometrics
arXiv:2609.09488 · PDF · Extracted main text
This paper studies difference-in-differences with staggered adoption and a continuous, time-invariant dose. Each cohort-time comparison contains two margins. The level margin is the average treatment effect at realized doses. Under level parallel trends it equals the level contrast between the treated cohort and not-yet-treated controls. The response margin is the within-cohort slope of the outcome change on dose. It uses no controls, and its causal interpretation requires a response parallel trends assumption and a restriction on selection on gains. We show that the continuous-dose OLS coefficient in each cohort-time comparison is a convex combination of the response index and the level contrast per unit of mean dose, with a mixing weight that depends on the not-yet-treated share. We provide estimators of both margins, joint inference across cohort-time comparisons and event-time aggregates, and a covariate-adjusted extension. In an application to hydraulic fracturing, the level leads reject a joint zero restriction, whereas the response-index leads do not. The continuous-dose OLS coefficient draws primarily on the level margin. We report the level and response margin separately.
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| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Callaway, Brantly and Goodman-Bacon, Andrew and Sant'Anna, Pedro H. C (2026) Difference-in-Differences with a Continuous Treatment | 0.956 | 8 | 5 | 88% |
| 2 | Bartik, Alexander W. and Currie, Janet and Greenstone, Michael and K… (2019) The Local Economic and Welfare Consequences of Hydraulic Fracturing | 0.874 | 5 | 2 | 100% |
| 3 | Callaway, Brantly and Goodman-Bacon, Andrew and Sant'Anna, Pedro H. C (2024) Event Studies with a Continuous Treatment | 0.737 | 3 | 2 | 100% |
| 4 | Clarke, Paul S. and Polselli, Annalivia (2026) Double Machine Learning for Static Panel Models with Fixed Effects | 0.644 | 2 | 2 | 100% |
| 5 | Goodman-Bacon, Andrew (2021) Difference-in-Differences with Variation in Treatment Timing | 0.644 | 2 | 2 | 100% |
| 6 | Rambachan, Ashesh and Roth, Jonathan (2023) A More Credible Approach to Parallel Trends | 0.644 | 2 | 2 | 100% |
| 7 | Hines, Oliver J. and Díaz-Ordaz, Karla and Vansteelandt, Stijn (2026) Parameterizing the Effect of a Continuous Treatment Using Average Derivative Effects | 0.585 | 4 | 3 | 25% |
| 8 | Jetsupphasuk, Michael and Fang, Chenwei and Li, Didong and Hudgens,… (2025) Difference-in-Differences with Stochastic Policy Shifts of a Continuous Treatment | 0.511 | 2 | 2 | 50% |
| 9 | Yitzhaki, Shlomo (1996) On Using Linear Regressions in Welfare Economics | 0.511 | 2 | 1 | 100% |
| 10 | Abadie, Alberto (2005) Semiparametric Difference-in-Differences Estimators | 0.405 | 1 | 1 | 100% |
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