Synthetic Interventions: Extending Synthetic Controls to Multiple Treatments
References
- (2021) Using synthetic controls: Feasibility, data requirements, and methodological aspects. J. Econom. Literature 59(2):391–425.Crossref, Google Scholar
- (2003) The economic costs of conflict: A case study of the Basque Country. Amer. Econom. Rev. 93(1):113–132.Crossref, Google Scholar
- (2010) Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. J. Amer. Statist. Assoc. 105(490):493–505.Crossref, Google Scholar
- (2022) Synthetic blip effects: Generalizing synthetic controls for the dynamic treatment regime. Preprint, submitted October 20, https://arxiv.org/abs/2210.11003.Google Scholar
- (2025) On model identification and out-of-sample prediction of PCR with applications to synthetic controls. J. Machine Learn. Res. 26(117):1–58.Google Scholar
- (2021) On robustness of principal component regression. J. Amer. Statist. Assoc. 116(536):1731–1745.Crossref, Google Scholar
- (2018) Robust synthetic control. J. Machine Learn. Res. 19(22):1–51.Google Scholar
- (2019) MRSC: Multi-dimensional robust synthetic control. Proc. ACM Measurement Anal. Comput. Syst. 3(2):37. Crossref, Google Scholar
- (2014) Tensor decompositions for learning latent variable models. J. Machine Learn. Res. 15(1):2773–2832.Google Scholar
- (2023) Large-sample properties of the synthetic control method under selection on unobservables. Preprint, submitted November 22, https://arxiv.org/abs/2311.13575.Google Scholar
- (2021) Synthetic difference-in-differences. Amer. Econom. Rev. 111(12):4088–4118.Crossref, Google Scholar
- (2021) Matrix completion methods for causal panel data models. J. Amer. Statist. Assoc. 116(536):1716–1730.Crossref, Google Scholar
- (2003) Inferential theory for factor models of large dimensions. Econometrica 71(1):135–171.Crossref, Google Scholar
- (2021) Matrix completion, counterfactuals, and factor analysis of missing data. J. Amer. Statist. Assoc. 116(536):1746–1763.Crossref, Google Scholar
- (2016) Noisy tensor completion via the sum-of-squares hierarchy. Feldman V, Rakhlin A, Shamir O, eds. Proc. 29th Annual Conf. Learn. Theory, Proceedings of Machine Learning Research, vol. 49 (JMLR.org), 417–445.Google Scholar
- (2021a) The augmented synthetic control method. J. Amer. Statist. Assoc. 116(536):1789–1803.Crossref, Google Scholar
- (2021b) Synthetic controls with staggered adoption. J. Roy. Statist. Soc. Ser. B: Stat. Methodol. 84(2):351–381.Crossref, Google Scholar
- (1998) Bayesian PCA. Kearns M, Solla S, Cohn D, eds. Advances in Neural Information Processing Systems, vol. 11 (MIT Press, Cambridge, MA), 382–388. Google Scholar
- (2024) A design-based perspective on synthetic control methods. J. Bus. Econom. Statist. 42(2):762–773.Crossref, Google Scholar
- (2013) Statistical significance in high-dimensional linear models. Bernoulli 19(4):1212–1242.Crossref, Google Scholar
- (2018) ArCo: An artificial counterfactual approach for high-dimensional panel time-series data. J. Econom. 207(2):352–380.Crossref, Google Scholar
- (2021) Prediction intervals for synthetic control methods. J. Amer. Statist. Assoc. 116(536):1865–1880.Crossref, Google Scholar
- (2022) Uncertainty quantification in synthetic controls with staggered treatment adoption. Preprint, submitted October 10, https://arxiv.org/abs/2210.05026.Google Scholar
- (1983) Arbitrage, factor structure, and mean-variance analysis on large asset markets. Econometrica 51(5):1281–1304.Crossref, Google Scholar
- (2015) Matrix estimation by universal singular value thresholding. Ann. Statist. 43(1):177–214.Crossref, Google Scholar
- (2018) Debiasing and t-tests for synthetic control inference on average causal effects. Preprint, submitted December 27, https://arxiv.org/abs/1812.10820.Google Scholar
- (2021) An exact and robust conformal inference method for counterfactual and synthetic controls. J. Amer. Statist. Assoc. 116(536):1849–1864.Crossref, Google Scholar
- (2016) Balancing, regression, difference-in-differences and synthetic control methods: A synthesis. NBER Working Paper No. 22791, National Bureau of Economic Research, Cambridge, MA.Google Scholar
- (2018) An eigenvector perturbation bound and its application to robust covariance estimation. J. Machine Learn. Res. 18(207):1–42.Google Scholar
- (2011) Tensor completion and low—Rank tensor recovery via convex optimization. Inverse Problems 27(2):025010.Crossref, Google Scholar
- (2014) The optimal hard threshold for singular values is 43. IEEE Trans. Inform. Theory 60(8):5040–5053.Crossref, Google Scholar
- (2012) A panel data approach for program evaluation: Measuring the benefits of political and economic integration of Hong Kong with mainland China. J. Appl. Econometrics 27(5):705–740.Crossref, Google Scholar
- (2015) Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (2018) Causal inference with noisy and missing covariates via matrix factorization. Bengio S, Wallach H, Larochelle H, Grauman K, Cesa-Bianchi N, Garnett R, eds. Advances in Neural Information Processing Systems, vol. 31 (Curran Associates, Red Hook, NY), 6921–6932.Google Scholar
- (2020) Statistical inference for average treatment effects estimated by synthetic control methods. J. Amer. Statist. Assoc. 115(532):2068–2083.Crossref, Google Scholar
- (2017) Estimation of average treatment effects with panel data: Asymptotic theory and implementation. J. Econom. 197(1):65–75.Crossref, Google Scholar
- (2009) Tensor completion for estimating missing values in visual data. 2009 IEEE 12th Internat. Conf. Comput. Vision (Institute of Electrical and Electronics Engineers, Piscataway, NJ), 2114–2121.Google Scholar
- (1974) Estimating causal effects of treatments in randomized and nonrandomized studies. J. Ed. Psych. 66(5):688–701.Crossref, Google Scholar
- (2021) Randomization tests in observational studies with staggered adoption of treatment. J. Amer. Statist. Assoc. 116(536):1835–1848.Crossref, Google Scholar
- (2023) Same root different leaves: Time series and cross-sectional methods in panel data. Econometrica 91(6):2125–2154.Crossref, Google Scholar
- (1990) On the application of probability theory to agricultural experiments. Essay on principles. Section 9. Statist. Sci. 5(4):465–472. Translated and edited by Dabrowska DM and Speed TP.Google Scholar
- (1999) Probabilistic principal component analysis. J. Roy. Statist. Soc. Ser. B: Statist. Methodology 61(3):611–622.Crossref, Google Scholar
- (2017) Nice latent variable models have log-rank.Google Scholar
- (2019) Why are big data matrices approximately low rank? SIAM J. Math. Data Sci. 1(1):144–160.Crossref, Google Scholar
- (2018) Rates of convergence of spectral methods for graphon estimation. Dy J, Krause A, eds. Proc. 35th Internat. Conf. Machine Learn., Proceedings of Machine Learning Research, vol. 80 (JMLR.org), 5433–5442.Google Scholar

