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When researchers develop new econometric methods it is common practice to compare the performance of the new methods to those of existing methods in Monte Carlo studies.
Estimation and inference in nonlinear structural models
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Applied nonparametric regression
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On the role of the propensity score in efficient semiparametric estimation of average treatment effects
Jinyong Hahn · 1998
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Improved rates and asymptotic normality for nonparametric neural network estimators
Xiaohong Chen and Halbert White · 1999
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Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs
Rajeev H Dehejia and Sadek Wahba · 1999
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Comments and rejoinder
DO Scharfstein, A Rotnitzky, and JM Robins · 1999
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Propensity score-matching methods for nonexperimental causal studies
Rajeev H Dehejia and Sadek Wahba · 2002
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Efficient estimation of average treatment effects using the estimated propensity score
Keisuke Hirano, Guido W Imbens, and Geert Ridder · 2003
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Nonparametric estimation of average treatment effects under exogeneity: A review
Guido Imbens · 2004
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Large sample properties of matching estimators for average treatment effects
Alberto Abadie and Guido W Imbens · 2006
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Introduction to nonparametric estimation
Alexandre B Tsybakov · 2008
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Dealing with limited overlap in estimation of average treatment effects
Richard K Crump, V Joseph Hotz, Guido W Imbens, and Oscar A Mitnik · 2009
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Large-scale machine learning with stochastic gradient descent
Léon Bottou · 2010
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Robust inference using inverse probability weighting
Xinwei Ma and Jingshen Wang · 2010
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Bias-corrected matching estimators for average treatment effects
Alberto Abadie and Guido W Imbens · 2011
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Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi · 2013
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The performance of estimators based on the propensity score
Martin Huber, Michael Lechner, and Conny Wunsch · 2013
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Sensitivity of matching-based program evaluations to the availability of control variables
Michael Lechner and Conny Wunsch · 2013
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Dropout training as adaptive regularization
Stefan Wager, Sida Wang, and Percy S Liang · 2013
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An empirical analysis of dropout in piecewise linear networks
David Warde-Farley, Ian J Goodfellow, Aaron Courville, and Yoshua Bengio · 2013
Conditional image synthesis with auxiliary classifier gans
Augustus Odena, Christopher Olah, and Jonathon Shlens · 2017
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Synth-validation: Selecting the best causal inference method for a given dataset
Alejandro Schuler, Ken Jung, Robert Tibshirani, Trevor Hastie, and Nigam Shah · 2017
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Econometric methods for program evaluation
Alberto Abadie and Matias D Cattaneo · 2018
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Approximate residual balancing: debiased inference of average treatment effects in high dimensions
Susan Athey, Guido W Imbens, and Stefan Wager · 2018
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The econometrics of shape restrictions
Denis Chetverikov, Andres Santos, and Azeem M Shaikh · 2018
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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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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero · 2014
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The loss surfaces of multilayer networks
Anna Choromanska, Mikael Henaff, Michael Mathieu, Gérard Ben Arous, and Yann LeCun · 2015
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Robust inference on average treatment effects with possibly more covariates than observations
Max H. Farrell · 2015
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Max H Farrell, Tengyuan Liang, and Sanjog Misra · 2018
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Machine learning estimation of heterogeneous causal effects: Empirical monte carlo evidence
Michael Knaus, Michael Lechner, and Anthony Strittmatter · 2018
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Auto-painter: Cartoon image generation from sketch by using conditional wasserstein generative adversarial networks
Yifan Liu, Zengchang Qin, Tao Wan, and Zhenbo Luo · 2018
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Density estimation for statistics and data analysis
Bernard W Silverman · 2018
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Nonparametric density estimation under adversarial losses
Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, and Barnabás Póczos · 2018
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Estimation and inference of heterogeneous treatment effects using random forests
Stefan Wager and Susan Athey · 2018
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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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Differentially private generative adversarial network, 2018
Liyang Xie, Kaixiang Lin, Shu Wang, Fei Wang, and Jiayu Zhou · 2018
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Mostly harmless simulations? using monte carlo studies for estimator selection
Arun Advani, Toru Kitagawa, and Tymon Słoczynński · 2019
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Testing regression monotonicity in econometric models
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Artificial intelligence for structural estimation
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Practical procedures to deal with common support problems in matching estimation
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