Theory for Identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework.

Shi X, Li KQ, Yu M, Miao W, Kuchibhotla AK, Hu M, Tchetgen ET

DOI: 10.1080/01621459.2026.2639734
Published: 2026 Jun 4
Container: Journal of the American Statistical Association
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1080/01621459.2026.2639734,
  title = {Theory for Identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework.},
  author = {Shi X and Li KQ and Yu M and Miao W and Kuchibhotla AK and Hu M and Tchetgen ET},
  year = {2026},
  journal = {Journal of the American Statistical Association},
  doi = {10.1080/01621459.2026.2639734},
  url = {https://doi.org/10.1080/01621459.2026.2639734}
}

RIS

TY  - JOUR
TI  - Theory for Identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework.
AU  - Shi X
AU  - Li KQ
AU  - Yu M
AU  - Miao W
AU  - Kuchibhotla AK
AU  - Hu M
AU  - Tchetgen ET
PY  - 2026
JO  - Journal of the American Statistical Association
DO  - 10.1080/01621459.2026.2639734
UR  - https://doi.org/10.1080/01621459.2026.2639734
ER  -

APA

X, S., KQ, L., M, Y., W, M., AK, K., M, H., & ET, T. (2026). Theory for Identification and Inference with Synthetic Controls: A Proximal Causal Inference Framework.. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2026.2639734

Source records

pubmed · retrieved 2026-09-26T15:44:03.607Z