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Approximate Residual Balancing: De-Biased Inference of Average Treatment
  Effects in High Dimensions

Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions

25 April 2016
Susan Athey
Guido Imbens
Stefan Wager
    CML
ArXivPDFHTML

Papers citing "Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions"

11 / 111 papers shown
Title
Targeted Undersmoothing
Targeted Undersmoothing
Christian B. Hansen
Damian Kozbur
S. Misra
19
13
0
22 Jun 2017
Bias and high-dimensional adjustment in observational studies of peer
  effects
Bias and high-dimensional adjustment in observational studies of peer effects
Dean Eckles
E. Bakshy
9
61
0
14 Jun 2017
Minimal Dispersion Approximately Balancing Weights: Asymptotic
  Properties and Practical Considerations
Minimal Dispersion Approximately Balancing Weights: Asymptotic Properties and Practical Considerations
Yixin Wang
J. Zubizarreta
25
109
0
02 May 2017
Policy Learning with Observational Data
Policy Learning with Observational Data
Susan Athey
Stefan Wager
CML
OffRL
9
183
0
09 Feb 2017
Balancing, Regression, Difference-In-Differences and Synthetic Control
  Methods: A Synthesis
Balancing, Regression, Difference-In-Differences and Synthetic Control Methods: A Synthesis
Nikolay Doudchenko
Guido Imbens
28
410
0
25 Oct 2016
Panning for Gold: Model-X Knockoffs for High-dimensional Controlled
  Variable Selection
Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection
E. Candès
Yingying Fan
Lucas Janson
Jinchi Lv
40
365
0
07 Oct 2016
Generalized Random Forests
Generalized Random Forests
Susan Athey
J. Tibshirani
Stefan Wager
25
1,332
0
05 Oct 2016
Locally Robust Semiparametric Estimation
Locally Robust Semiparametric Estimation
Victor Chernozhukov
J. Escanciano
Hidehiko Ichimura
Whitney Newey
J. M. Robins
17
203
0
29 Jul 2016
High-dimensional regression adjustments in randomized experiments
High-dimensional regression adjustments in randomized experiments
Stefan Wager
Wenfei Du
Jonathan E. Taylor
Robert Tibshirani
16
116
0
22 Jul 2016
Kernel Balancing: A flexible non-parametric weighting procedure for
  estimating causal effects
Kernel Balancing: A flexible non-parametric weighting procedure for estimating causal effects
Chad Hazlett
CML
8
27
0
30 Apr 2016
SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax
SLOPE is Adaptive to Unknown Sparsity and Asymptotically Minimax
Weijie Su
Emmanuel Candes
65
145
0
29 Mar 2015
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