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The synthetic controls (SC) methodology is a prominent tool for policy evaluation in panel data applications.
Sur les applications de la theorie des probabilites aux experiences agricoles: Essai des principes
Jerzy Neyman · 1923
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Perturbation bounds in connection with singular value decomposition
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Estimating causal effects of treatments in randomized and nonrandomized studies
Donald B. Rubin · 1974
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Arbitrage, factor structure, and mean-variance analysis on large asset markets
Gary Chamberlain and Michael Rothschild · 1983
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Probability and Measure
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Bayesian pca
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Probabilistic principal component analysis
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The economic costs of conflict: A case study of the basque country
A. Abadie and J. Gardeazabal · 2003
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Inferential theory for factor models of large dimensions
Jushan Bai · 2003
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Tensor completion for estimating missing values in visual data
Ji Liu, P. Musialski, P. Wonka, and Jieping Ye · 2009
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Synthetic control methods for comparative case studies: Estimating the effect of californiaâs tobacco control program
A. Abadie, A. Diamond, and J. Hainmueller · 2010
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Tensor completion and low—rank tensor recovery via convex optimization
Silvia Gandy, Benjamin Recht, and Isao Yamada · 2011
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A panel data approach for program evaluation: Measuring the benefits of political and economic integration of hong kong with mainland china
Cheng Hsiao, H. Steve Ching, and Shui Ki Wan · 2012
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The optimal hard threshold for singular values is
David Donoho and Matan Gavish · 2013
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Tensor decompositions for learning latent variable models
Animashree Anandkumar, Rong Ge, Daniel Hsu, Sham M. Kakade, and Matus Telgarsky · 2014
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Matrix estimation by universal singular value thresholding
Sourav Chatterjee · 2015
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Matrix estimation by universal singular value thresholding
Sourav Chatterjee · 2015
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Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Guido W. Imbens and Donald B. Rubin · 2015
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The state of applied econometrics - causality and policy evaluation
S. Athey and G. Imbens · 2016
Cited alongside, same era.
Noisy tensor completion via the sum-of-squares hierarchy
Boaz Barak and Ankur Moitra · 2016
Cited alongside, same era.
Balancing, regression, difference-in-differences and synthetic control methods: A synthesis
N. Doudchenko and G. Imbens · 2016
Cited alongside, same era.
Iterative collaborative filtering for sparse noisy tensor estimation
D. Shah and C. L. Yu · 2019
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Why are big data matrices approximately low rank?
Madeleine Udell and Alex Townsend · 2019
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Using synthetic controls: Feasibility, data requirements, and methodological aspects
Alberto Abadie · 2020
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Practical and robust t t -test based inference for synthetic control and related methods, 2020
Victor Chernozhukov, Kaspar Wuthrich, and Yinchu Zhu · 2020
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Statistical inference for average treatment effects estimated by synthetic control methods
Kathleen T. Li · 2020
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Synthetic difference-in-differences
Dmitry Arkhangelsky, Susan Athey, David A. Hirshberg, Guido W. Imbens, and Stefan Wager · 2021
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Estimation of average treatment effects with panel data: Asymptotic theory and implementation
Kathleen T. Li and David R. Bell · 2017
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Nice latent variable models have log-rank
Madeleine Udell and A. Townsend · 2017
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Robust synthetic control
Muhammad Jehangir Amjad, Devavrat Shah, and Dennis Shen · 2018
Cited alongside, same era.
Arco: An artificial counterfactual approach for high-dimensional panel time-series data
Carlos Carvalho, Ricardo Masini, and Marcelo C. Medeiros · 2018
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An eigenvector perturbation bound and its application to robust covariance estimation
Jianqing Fan, Weichen Wang, and Yiqiao Zhong · 2018
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Causal inference with noisy and missing covariates via matrix factorization
Nathan Kallus, Xiaojie Mao, and Madeleine Udell · 2018
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Matrix completion methods for causal panel data models
Susan Athey, Mohsen Bayati, Nikolay Doudchenko, Guido Imbens, and Khashayar Khosravi · 2021
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On robustness of principal component regression
Anish Agarwal, Devavrat Shah, Dennis Shen, and Dogyoon Song · 2021
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The augmented synthetic control method
Eli Ben-Michael, Avi Feller, and Jesse Rothstein · 2021
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Matrix completion, counterfactuals, and factor analysis of missing data
Jushan Bai and Serena Ng · 2021
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An exact and robust conformal inference method for counterfactual and synthetic controls
Victor Chernozhukov, Kaspar Wüthrich, and Yinchu Zhu · 2021
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Causal imputation via synthetic interventions
Chandler Squires, Dennis Shen, Anish Agarwal, Devavrat Shah, and Caroline Uhler · 2022
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Synthetic combinations: A causal inference framework for combinatorial interventions
Abhineet Agarwal, Anish Agarwal, and Suhas Vijaykumar · 2023
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On principal component regression in a high-dimensional error-in-variables setting, 2023
Anish Agarwal, Devavrat Shah, and Dennis Shen · 2023
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A design-based perspective on synthetic control methods
Jann Spiess Lea Bottmer, Guido W. Imbens and Merrill Warnick · 2024
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