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Large-Sample Properties of the Synthetic Control Method under Selection on Unobservables

Dmitry Arkhangelsky, David Hirshberg

arXiv 22 Nov 2023 · Econometrics · 5 citations (OpenAlex)

arXiv:2311.13575 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We analyze the synthetic control (SC) method in panel data settings with many units. We assume the treatment assignment is based on unobserved heterogeneity and pre-treatment information, allowing for both strictly and sequentially exogenous assignment processes. We show that the critical property that determines the behavior of the SC method is the ability of input features to approximate the unobserved heterogeneity. Our results imply that the SC method delivers asymptotically normal estimators for a large class of linear panel data models as long as the number of pre-treatment periods is sufficiently large, making it a natural alternative to the Difference-in-Differences.

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Most heavily cited references

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.

ReferenceIntensityMentionsSectionsMain text
1Alberto Abadie, Alexis Diamond, and Jens Hainmueller (2010) Synthetic control methods for comparative case studies: Estimating the effect of California's tobacco control program1.00073100%
2Dmitry Arkhangelsky, Susan Athey, David A Hirshberg, Guido W Imbens,… (2021) Synthetic difference-in-differences self0.92844100%
3Brantly Callaway and Pedro HC Sant’Anna (2021) Difference-in-differences with multiple time periods0.87452100%
4Manuel Arellano (2003) Panel data econometrics0.84333100%
5Jushan Bai (2009) Panel data models with interactive fixed effects0.81142100%
6Yixin Wang and Jose R Zubizarreta (2020) Minimal dispersion approximately balancing weights: asymptotic properties and practical considerations0.7373367%
7Orley Ashenfelter and David Card (1985) Using the longitudinal structure of earnings to estimate the effect of training programs0.73732100%
8Hugo Freeman and Martin Weidner (2023) Linear panel regressions with two-way unobserved heterogeneity0.73732100%
9Dalia Ghanem, Pedro HC Sant'Anna, and Kaspar Wüthrich (2022) Selection and parallel trends0.73732100%
10Liyang Sun and Sarah Abraham (2021) Estimating dynamic treatment effects in event studies with heterogeneous treatment effects0.73732100%

Showing the top 10 of 80 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Causal Models for Longitudinal and Panel Data: A Survey1.00053
22206.017790.40511
3Identification and Inference for Synthetic Controls with Confounding0.40511
4Inference for Synthetic Controls via Refined Placebo Tests0.40511
5Inference after discretizing time-varying unobserved heterogeneity0.40511
6A Relaxation Approach to Synthetic Control0.40511
7Debiasing and $t$-tests for synthetic control inference on average causal effects0.00011