Dmitry Arkhangelsky, Susan Athey, David A. Hirshberg, Guido W. Imbens, Stefan Wager
arXiv 24 Dec 2018 · Statistics — Methodology · publishedAmerican Economic Review (2021) · 90 citations (OpenAlex)
arXiv:1812.09970 · PDF · DOI · OpenAlex · Extracted main text
We present a new estimator for causal effects with panel data that builds on insights behind the widely used difference in differences and synthetic control methods. Relative to these methods we find, both theoretically and empirically, that this "synthetic difference in differences" estimator has desirable robustness properties, and that it performs well in settings where the conventional estimators are commonly used in practice. We study the asymptotic behavior of the estimator when the systematic part of the outcome model includes latent unit factors interacted with latent time factors, and we present conditions for consistency and asymptotic normality.
appendix boundary found by appendix_titled_section at “Appendix” · 56% 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 | Alberto Abadie, Alexis Diamond, and Jens Hainmueller (2010) Synthetic control methods for comparative case studies: Estimating the effect of California's tobacco control program | 1.000 | 10 | 5 | 100% |
| 2 | Marianne Bertrand, Esther Duflo, and Sendhil Mullainathan (2004) How much should we trust differences-in-differences estimates? | 1.000 | 9 | 3 | 100% |
| 3 | Jushan Bai (2009) Panel data models with interactive fixed effects | 1.000 | 6 | 3 | 100% |
| 4 | Hyungsik Roger Moon and Martin Weidner (2015) Linear regression for panel with unknown number of factors as interactive fixed effects | 1.000 | 6 | 3 | 100% |
| 5 | Alberto Abadie, Alexis Diamond, and Jens Hainmueller (2015) Comparative politics and the synthetic control method | 1.000 | 5 | 4 | 100% |
| 6 | HR Moon and M Weidner (2017) Dynamic linear panel regression models with interactive fixed effects | 1.000 | 5 | 3 | 100% |
| 7 | Susan Athey, Mohsen Bayati, Nikolay Doudchenko, Guido Imbens, and Kh… (2017) Matrix completion methods for causal panel data models self | 0.950 | 7 | 5 | 86% |
| 8 | Nikolay Doudchenko and Guido W Imbens (2016) Balancing, regression, difference-in-differences and synthetic control methods: A synthesis self | 0.928 | 4 | 4 | 100% |
| 9 | Bruno Ferman and Cristine Pinto (2019) Synthetic controls with imperfect pre-treatment fit | 0.928 | 4 | 3 | 100% |
| 10 | Yiqing Xu (2017) Generalized synthetic control method: Causal inference with interactive fixed effects models | 0.928 | 4 | 3 | 100% |
Showing the top 10 of 64 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Synthetic Parallel Trends | 1.000 | 33 | 5 |
| 2 | Efficient Difference-in-Differences and Event Study Estimators | 1.000 | 24 | 4 |
| 3 | Identification and Inference for Synthetic Controls with Confounding | 1.000 | 14 | 5 |
| 4 | Triply Robust Panel Estimators | 1.000 | 14 | 4 |
| 5 | Sequential Synthetic Difference in Differences | 1.000 | 7 | 4 |
| 6 | Causal Models for Longitudinal and Panel Data: A Survey | 1.000 | 6 | 3 |
| 7 | A Way to Synthetic Triple Difference | 1.000 | 6 | 3 |
| 8 | Synthetic Difference in Differences for Repeated Cross-Sectional Data | 1.000 | 6 | 3 |
| 9 | Correlated Synthetic Controls | 1.000 | 5 | 3 |
| 10 | Estimating Variances for Causal Panel Data Estimators | 1.000 | 5 | 3 |