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Inference in Linear Regression Models with Many Covariates and
  Heteroskedasticity
v1v2 (latest)

Inference in Linear Regression Models with Many Covariates and Heteroskedasticity

Journal of the American Statistical Association (JASA), 2015
9 July 2015
M. D. Cattaneo
Michael Jansson
Whitney Newey
ArXiv (abs)PDFHTML

Papers citing "Inference in Linear Regression Models with Many Covariates and Heteroskedasticity"

28 / 28 papers shown
Estimation in high-dimensional linear regression: Post-Double-Autometrics as an alternative to Post-Double-Lasso
Estimation in high-dimensional linear regression: Post-Double-Autometrics as an alternative to Post-Double-Lasso
Sullivan Hué
S. Laurent
Ulrich Aiounou
Emmanuel Flachaire
237
0
0
26 Nov 2025
Applied Causal Inference Powered by ML and AI
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov
Christian Hansen
Nathan Kallus
Martin Spindler
Vasilis Syrgkanis
CML
438
57
0
04 Mar 2024
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
126
2
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})d=o(n1/2)
Woonyoung Chang
Arun K. Kuchibhotla
Alessandro Rinaldo
271
4
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 estimatorsJournal of Econometrics (J. Econometrics), 2023
Lin Liu
Rajarshi Mukherjee
J. M. Robins
551
5
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
327
1
0
07 May 2023
Testing Many Zero Restrictions in a High Dimensional Linear Regression
  Setting
Testing Many Zero Restrictions in a High Dimensional Linear Regression Setting
Jonathan B. Hill
330
2
0
22 Jan 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 EstimatorsJournal of Econometrics (JE), 2022
M. D. Cattaneo
M. Farrell
Michael Jansson
Ricardo P. Masini
195
3
0
31 Dec 2022
Treatment Effect Estimation with Efficient Data Aggregation
Treatment Effect Estimation with Efficient Data AggregationBernoulli (Bernoulli), 2022
Snigdha Panigrahi
Jingshen Wang
Xuming He
421
3
0
23 Mar 2022
Posterior Inference for Quantile Regression: Adaptation to Sparsity
Posterior Inference for Quantile Regression: Adaptation to Sparsity
Yuanzhi Li
Xuming He
248
0
0
01 Nov 2021
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 parametersStatistical Science (Statist. Sci.), 2021
Niloofar Moosavi
J. Haggstrom
X. de Luna
311
16
0
05 May 2021
Valid Heteroskedasticity Robust Testing
Valid Heteroskedasticity Robust TestingEconometric Theory (ET), 2021
B. M. Potscher
David Preinerstorfer
207
4
0
26 Apr 2021
Testing (Infinitely) Many Zero Restrictions
Testing (Infinitely) Many Zero Restrictions
Jonathan B. Hill
370
0
0
03 Nov 2020
Deep Learning for Individual Heterogeneity
Deep Learning for Individual Heterogeneity
M. Farrell
Tengyuan Liang
S. Misra
BDL
517
17
0
28 Oct 2020
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
156
0
0
22 Oct 2020
Empirical likelihood and uniform convergence rates for dyadic kernel
  density estimation
Empirical likelihood and uniform convergence rates for dyadic kernel density estimation
Harold D. Chiang
Bing Tan
498
4
0
17 Oct 2020
On rank estimators in increasing dimensions
On rank estimators in increasing dimensionsJournal of Econometrics (JE), 2019
Yanqin Fan
Fang Han
Wei Li
Xiao‐Hua Zhou
454
19
0
14 Aug 2019
Competing Models
Competing Models
J. M. Olea
Pietro Ortoleva
Mallesh M. Pai
A. Prat
180
48
0
08 Jul 2019
Omitted variable bias of Lasso-based inference methods: A finite sample
  analysis
Omitted variable bias of Lasso-based inference methods: A finite sample analysisReview of Economics and Statistics (REStat), 2019
Kaspar Wüthrich
Ying Zhu
949
34
0
20 Mar 2019
On Binscatter
On Binscatter
M. D. Cattaneo
Richard K. Crump
M. Farrell
Yingjie Feng
393
160
0
25 Feb 2019
Statistical inference with F-statistics when fitting simple models to
  high-dimensional data
Statistical inference with F-statistics when fitting simple models to high-dimensional dataEconometric Theory (ET), 2019
Hannes Leeb
Lukas Steinberger
187
1
0
12 Feb 2019
Heteroskedasticity-robust inference in linear regression models with
  many covariates
Heteroskedasticity-robust inference in linear regression models with many covariates
Koen Jochmans
133
4
0
17 Sep 2018
Automatic Debiased Machine Learning of Causal and Structural Effects
Automatic Debiased Machine Learning of Causal and Structural Effects
Victor Chernozhukov
Whitney Newey
Rahul Singh
CMLAI4CE
747
146
0
14 Sep 2018
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
255
67
0
26 Jul 2018
Robust Inference Under Heteroskedasticity via the Hadamard Estimator
Robust Inference Under Heteroskedasticity via the Hadamard Estimator
Guang Cheng
Weijie J. Su
Yachong Yang
Zhixiang Zhang
139
7
0
01 Jul 2018
Regression adjustment in completely randomized experiments with a
  diverging number of covariates
Regression adjustment in completely randomized experiments with a diverging number of covariates
Lihua Lei
Peng Ding
376
44
0
20 Jun 2018
High-Dimensional Econometrics and Regularized GMM
High-Dimensional Econometrics and Regularized GMM
A. Belloni
Victor Chernozhukov
Denis Chetverikov
Christian B. Hansen
Kengo Kato
409
69
0
05 Jun 2018
Semiparametric Efficient Empirical Higher Order Influence Function
  Estimators
Semiparametric Efficient Empirical Higher Order Influence Function Estimators
Lin Liu
Rajarshi Mukherjee
Whitney Newey
J. M. Robins
453
41
0
22 May 2017
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