arXiv 15 Aug 2018 · Econometrics · publishedJournal of Econometrics (2018) · 194 citations (OpenAlex)
arXiv:1808.05293 · PDF · DOI · OpenAlex · Extracted main text
In this paper we study estimation of and inference for average treatment effects in a setting with panel data. We focus on the setting where units, e.g., individuals, firms, or states, adopt the policy or treatment of interest at a particular point in time, and then remain exposed to this treatment at all times afterwards. We take a design perspective where we investigate the properties of estimators and procedures given assumptions on the assignment process. We show that under random assignment of the adoption date the standard Difference-In-Differences estimator is is an unbiased estimator of a particular weighted average causal effect. We characterize the proeperties of this estimand, and show that the standard variance estimator is conservative.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
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 | Sarah Abraham and Liyang Sun (2018) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects | 1.000 | 11 | 4 | 100% |
| 2 | Clément de Chaisemartin and Xavier D'Haultfuille (2018) Two-way fixed effects estimators with heterogeneous treatment effects | 1.000 | 9 | 3 | 100% |
| 3 | Kirill Borusyak and Xavier Jaravel (2016) Revisiting event study designs | 0.928 | 4 | 3 | 100% |
| 4 | Guido W Imbens and Donald B Rubin (2015) Causal Inference in Statistics, Social, and Biomedical Sciences self | 0.928 | 4 | 3 | 100% |
| 5 | Andrew Goodman-Bacon (2017) Difference-in-differences with variation in treatment timing | 0.874 | 5 | 2 | 100% |
| 6 | Chad Hazlett and Yiqing Xu (2018) Trajectory balancing: A general reweighting approach to causal inference with time-series cross-sectional data | 0.843 | 3 | 3 | 100% |
| 7 | Jerzey Neyman (1923) On the application of probability theory to agricultural experiments. essay on principles. section 9 | 0.843 | 3 | 3 | 100% |
| 8 | Marianne Bertrand, Esther Duflo, and Sendhil Mullainathan (2004) How much should we trust differences-in-differences estimates? | 0.811 | 4 | 2 | 100% |
| 9 | Alberto Abadie, Susan Athey, Guido W Imbens, and Jeffrey M Wooldridge (2017) Sampling-based vs. design-based uncertainty in regression analysis self | 0.644 | 2 | 2 | 100% |
| 10 | Joshua Angrist and Steve Pischke (2008) Mostly Harmless Econometrics: An Empiricists' Companion | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 41 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.