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For treatment effects - one of the core issues in modern econometric analysis - prediction and estimation are two sides of the same coin.
Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study
Jared K Lunceford and Marie Davidian · 1903
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A generalization of sampling without replacement from a finite universe
Daniel G Horvitz and Donovan J Thompson · 1952
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Donald B Rubin · 1980
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Peter J Bickel · 1982
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Anton Schick · 1986
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401 (k) plans and tax-deferred saving
James M Poterba and Steven F Venti · 1994
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Behram Hansotia and Brad Rukstales · 2002
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The effects of 401 (k) participation on the wealth distribution: an instrumental quantile regression analysis
Victor Chernozhukov and Christian Hansen · 2004
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Propensity score estimation with boosted regression for evaluating causal effects in observational studies
Daniel F McCaffrey, Greg Ridgeway, and Andrew R Morral · 2004
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Bart: Bayesian additive regression trees
Hugh A Chipman, Edward I George, Robert E McCulloch, et al · 2010
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Targeted maximum likelihood based causal inference: Part i
Mark J van der Laan · 2010
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Subgroup identification from randomized clinical trial data
Jared C Foster, Jeremy MG Taylor, and Stephen J Ruberg · 2011
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Bayesian nonparametric modeling for causal inference
Jennifer L Hill · 2011
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Eric C Polley, Sherri Rose, and Mark J Van der Laan · 2011
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New statistical approaches to semiparametric regression with application to air pollution research
James M Robins, Peng Zhang, Rajeev Ayyagari, Roger Logan, Eric Tchetgen Tchetgen, Lingling Li, Thomas Lumley, and Aad van der Vaart · 2013
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The role of prediction modeling in propensity score estimation: an evaluation of logistic regression, bcart, and the covariate-balancing propensity score
Richard Wyss, Alan R Ellis, M Alan Brookhart, Cynthia J Girman, Michele Jonsson Funk, Robert LoCasale, and Til Stürmer · 2014
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Estimating the impact of microcredit on those who take it up: Evidence from a randomized experiment in morocco
Bruno Crépon, Florencia Devoto, Esther Duflo, and William Parienté · 2015
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Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases
T Wendling, K Jung, A Callahan, A Schuler, NH Shah, and B Gallego · 2018
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The impact of machine learning on economics
Susan Athey · 2019
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Generalized random forests
Susan Athey, Stefan Wager, and Julie Tibshirani · 2019
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EconML: A Python Package for ML-Based Heterogeneous Treatment Effects Estimation
Microsoft Research EconML · 2019
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Estimation of conditional average treatment effects with high-dimensional data
Qingliang Fan, Yu-Chin Hsu, Robert P Lieli, and Yichong Zhang · 2019
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Metalearners for estimating heterogeneous treatment effects using machine learning
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Victor Chernozhukov, Juan Carlos Escanciano, Hidehiko Ichimura, Whitney K Newey, and James M Robins · 2016
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Susan Athey and Stefan Wager · 2017
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Machine learning: an applied econometric approach
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On the multiply robust estimation of the mean of the g-functional
Andrea Rotnitzky, James Robins, and Lucia Babino · 2017
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Estimation and inference of heterogeneous treatment effects using random forests
Stefan Wager and Susan Athey · 2017
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Rina Friedberg, Julie Tibshirani, Susan Athey, and Stefan Wager · 2018
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Cross-fitting and fast remainder rates for semiparametric estimation
Whitney K Newey and James R Robins · 2018
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Sören R Künzel, Jasjeet S Sekhon, Peter J Bickel, and Bin Yu · 2019
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DoWhy: A Python package for causal inference
Amit Sharma, Emre Kiciman, et al · 2019
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Bayesian regression tree models for causal inference: Regularization, confounding, and heterogeneous effects
P. Richard Hahn, Jared S. Murray, and Carlos M. Carvalho · 2020
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Cross-fitting and averaging for machine learning estimation of heterogeneous treatment effects
Daniel Jacob · 2020
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Optimal doubly robust estimation of heterogeneous causal effects
Edward H Kennedy · 2020
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Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence
Michael C Knaus, Michael Lechner, and Anthony Strittmatter · 2020
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Quasi-oracle estimation of heterogeneous treatment effects
X Nie and S Wager · 2020
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Deep neural networks for estimation and inference
Max H Farrell, Tengyuan Liang, and Sanjog Misra · 2021
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