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Two-Step Estimation and Inference with Possibly Many Included Covariates

Two-Step Estimation and Inference with Possibly Many Included Covariates

M. D. Cattaneo
Michael Jansson
Xinwei Ma
    CML
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Papers citing "Two-Step Estimation and Inference with Possibly Many Included Covariates"

17 / 17 papers shown
Title
Robust Inference in Panel Data Models: Some Effects of Heteroskedasticity and Leveraged Data in Small Samples
Robust Inference in Panel Data Models: Some Effects of Heteroskedasticity and Leveraged Data in Small Samples
Annalivia Polselli
19
1
0
29 Dec 2023
Inference for Projection Parameters in Linear Regression: beyond $d = o(n^{1/2})$
Inference for Projection Parameters in Linear Regression: beyond d=o(n1/2)d = o(n^{1/2})
Woonyoung Chang
Arun K. Kuchibhotla
Alessandro Rinaldo
84
3
0
03 Jul 2023
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators
Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators
Lin Liu
Rajarshi Mukherjee
J. M. Robins
78
2
0
18 Jun 2023
Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
Lin Liu
Yuhao Wang
72
0
0
07 May 2023
Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators
Higher-order Refinements of Small Bandwidth Asymptotics for Density-Weighted Average Derivative Estimators
M. D. Cattaneo
M. Farrell
Michael Jansson
Ricardo P. Masini
46
0
0
31 Dec 2022
Conditional Likelihood Ratio Test with Many Weak Instruments
Conditional Likelihood Ratio Test with Many Weak Instruments
Sreevidya Ayyar
Yukitoshi Matsushita
Taisuke Otsu
33
2
0
14 Oct 2022
The costs and benefits of uniformly valid causal inference with high-dimensional nuisance parameters
The costs and benefits of uniformly valid causal inference with high-dimensional nuisance parameters
Niloofar Moosavi
J. Haggstrom
X. de Luna
64
15
0
05 May 2021
Positive definiteness of the asymptotic covariance matrix of OLS estimators in parsimonious regressions
Positive definiteness of the asymptotic covariance matrix of OLS estimators in parsimonious regressions
Daisuke Nagakura
16
0
0
22 Oct 2020
Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data
Doubly Robust Semiparametric Difference-in-Differences Estimators with High-Dimensional Data
Y. Ning
Sida Peng
Jing Tao
60
5
0
07 Sep 2020
Causal Inference in Possibly Nonlinear Factor Models
Causal Inference in Possibly Nonlinear Factor Models
Yingjie Feng
CML
50
7
0
31 Aug 2020
Average Density Estimators: Efficiency and Bootstrap Consistency
Average Density Estimators: Efficiency and Bootstrap Consistency
M. D. Cattaneo
Michael Jansson
MDE
82
10
0
19 Apr 2019
Robust Inference Using Inverse Probability Weighting
Robust Inference Using Inverse Probability Weighting
Xinwei Ma
Jingshen Wang
78
95
0
26 Oct 2018
Deep Neural Networks for Estimation and Inference
Deep Neural Networks for Estimation and Inference
M. Farrell
Tengyuan Liang
S. Misra
BDL
186
256
0
26 Sep 2018
High-Dimensional Econometrics and Regularized GMM
High-Dimensional Econometrics and Regularized GMM
A. Belloni
Victor Chernozhukov
Denis Chetverikov
Christian B. Hansen
Kengo Kato
97
67
0
05 Jun 2018
Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation
Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation
Whitney Newey
Jamie Robins
102
148
0
27 Jan 2018
Targeted Undersmoothing
Targeted Undersmoothing
Christian B. Hansen
Damian Kozbur
S. Misra
65
13
0
22 Jun 2017
Locally Robust Semiparametric Estimation
Locally Robust Semiparametric Estimation
Victor Chernozhukov
J. Escanciano
Hidehiko Ichimura
Whitney Newey
J. M. Robins
138
210
0
29 Jul 2016