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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.
The jackknife-a review
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Bootstrap methods: Another look at the jackknife
Bradley Efron · 1979
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Using the longitudinal structure of earnings to estimate the effect of training programs
Orley Ashenfelter and David Card · 1985
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A comparison of the labor supply findings from the four negative income tax experiments
Philip K Robins · 1985
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Estimating vector autoregressions with panel data
Douglas Holtz-Eakin, Whitney Newey, and Harvey S Rosen · 1988
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The impact of the mariel boatlift on the miami labor market
David Card · 1990
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Efficiency bounds for semiparametric regression
Gary Chamberlain · 1992
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Estimation of regression coefficients when some regressors are not always observed
James M Robins, Andrea Rotnitzky, and Lue Ping Zhao · 1994
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Regression shrinkage and selection via the lasso
Robert Tibshirani · 1996
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Adjusting for nonignorable drop-out using semiparametric nonresponse models
Daniel O Scharfstein, Andrea Rotnitzky, and James M Robins · 1999
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GMM estimation of linear panel data models with time-varying individual effects
Seung Chan Ahn, Young Hoon Lee, and Peter Schmidt · 2001
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The economic costs of conflict: A case study of the basque country
Alberto Abadie and Javier Gardeazabal · 2003
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How much should we trust differences-in-differences estimates?
Marianne Bertrand, Esther Duflo, and Sendhil Mullainathan · 2004
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Nonparametric estimation of average treatment effects under exogeneity: A review
Guido Imbens · 2004
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Semiparametric difference-in-differences estimators
Alberto Abadie · 2005
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Mostly harmless econometrics: An empiricist’s companion
Joshua D Angrist and Jörn-Steffen Pischke · 2008
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Panel data models with interactive fixed effects
Jushan Bai · 2009
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Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program
Alberto Abadie, Alexis Diamond, and Jens Hainmueller · 2010
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Inference with“difference in difference” with a small number of policy changes
Timothy G Conley and Christopher R Taber · 2011
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Clustering, spatial correlations, and randomization inference
Thomas Barrios, Rebecca Diamond, Guido W Imbens, and Michal Kolesár · 2012
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Inverse probability tilting for moment condition models with missing data
Bryan Graham, Christine Pinto, and Daniel Egel · 2012
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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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Inference on treatment effects after selection among high-dimensional controls
Alexandre Belloni, Victor Chernozhukov, and Christian Hansen · 2014
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Covariate balancing propensity score
Kosuke Imai and Marc Ratkovic · 2014
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Confidence intervals for low dimensional parameters in high dimensional linear models
Cun-Hui Zhang and Stephanie S Zhang · 2014
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Comparative politics and the synthetic control method
Alberto Abadie, Alexis Diamond, and Jens Hainmueller · 2015
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Causal Inference in Statistics, Social, and Biomedical Sciences
Guido W Imbens and Donald B Rubin · 2015
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Linear regression for panel with unknown number of factors as interactive fixed effects
Hyungsik Roger Moon and Martin Weidner · 2015
Synthetic control method: Inference, sensitivity analysis and confidence sets
Sergio Firpo and Vitor Possebom · 2018
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Non-parametric panel data models with interactive fixed effects
Joachim Freyberger · 2018
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Nuclear norm regularized estimation of panel regression models
Hyungsik Roger Moon and Martin Weidner · 2018
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Pre-test with caution: Event-study estimates after testing for parallel trends
Jonathan Roth · 2018
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High-dimensional probability: An introduction with applications in data science , volume 47
Roman Vershynin · 2018
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Stable weights that balance covariates for estimation with incomplete outcome data
Jose R. Zubizarreta · 2015
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A penalized synthetic control estimator for disaggregated data, 2016
Alberto Abadie and Jérémy L’Hour · 2016
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Revisiting event study designs
Kirill Borusyak and Xavier Jaravel · 2016
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Balancing, regression, difference-in-differences and synthetic control methods: A synthesis
Nikolay Doudchenko and Guido W Imbens · 2016
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Regional policy evaluation: Interactive fixed effects and synthetic controls
Laurent Gobillon and Thierry Magnac · 2016
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Synthetic control and inference
Jinyong Hahn and Ruoyao Shi · 2016
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Anish Agarwal, Devavrat Shah, Dennis Shen, and Dogyoon Song · 2019
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Synthetic controls and weighted event studies with staggered adoption
Eli Ben-Michael, Avi Feller, and Jesse Rothstein · 2019
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Synthetic controls with imperfect pre-treatment fit
Bruno Ferman and Cristine Pinto · 2019
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Pre-event trends in the panel event-study design
Simon Freyaldenhoven, Christian Hansen, and Jesse M Shapiro · 2019
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The labor market effects of a refugee wave synthetic control method meets the mariel boatlift
Giovanni Peri and Vasil Yasenov · 2019
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An honest approach to parallel trends
Ashesh Rambachan and Jonathan Roth · 2019
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Covariate balancing propensity score by tailored loss functions
Qingyuan Zhao · 2019
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Difference-in-differences with multiple time periods
Brantly Callaway and Pedro Sant’anna · 2020
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The PCDID approach: Difference-in-differences when trends are potentially unparallel and stochastic
Mark K Chan and Simon Kwok · 2020
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Technology and big data are changing economics: Mining text to track methods
Janet Currie, Henrik Kleven, and Esmée Zwiers · 2020
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Two-way fixed effects estimators with heterogeneous treatment effects
Clément de Chaisemartin and Xavier d’Haultfœuille · 2020
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Generalized optimal matching methods for causal inference
Nathan Kallus · 2020
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Combining matching and synthetic control to trade off biases from extrapolation and interpolation
Maxwell Kellogg, Magne Mogstad, Guillaume Pouliot, and Alexander Torgovitsky · 2020
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Design-based analysis in difference-in-differences settings with staggered adoption
Susan Athey and Guido W Imbens · 2021
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A design-based perspective on synthetic control methods
Lea Bottmer, Guido Imbens, Jann Spiess, and Merrill Warnick · 2021
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Least squares with error in variables
David A Hirshberg · 2021
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